Vessels can be recognised by their navigation radar due to the characteristics of the emitted radar signal. This is particularly useful if one wants to build situational awareness without revealing one's own presence. Most countries maintain databases of radar fingerprints but will not readily share these due to national security regulations. Sharing of such information will generally require some form of information exchange agreement. However, all parties in a coalition benefit from correct identification. We use secure multiparty computation to match a radar signal measurement against secret databases and output plausible matches with their likelihoods. We also provide a demonstrator using MP-SPDZ.

Over years of the development of secure multi-party computation (MPC), many sophisticated functionalities have been made pratical and multi-dimensional operations occur more and more frequently in MPC protocols, especially in protocols involving datasets of vector elements, such as privacy-preserving biometric identification and privacy-preserving machine learning. In this paper, we introduce a new kind of correlation, called tensor triples, which is designed to make multi-dimensional MPC protocols more efficient. We will discuss the generation process, the usage, as well as the applications of tensor triples and show that it can accelerate privacy-preserving biometric identification protocols, such as FingerCode, Eigenfaces and FaceNet, by more than 1000 times, with reasonable offline costs.

In this work, we introduce the sparse LWE assumption, an assumption that draws inspiration from both Learning with Errors (Regev JACM 10) and Sparse Learning Parity with Noise (Alekhnovich FOCS 02). Exactly like LWE, this assumption posits indistinguishability of $(\mathbf{A}, \mathbf{s}\mathbf{A}+\mathbf{e} \mod p)$ from $(\mathbf{A}, \mathbf{u})$ for a random $\mathbf{u}$ where the secret $\mathbf{s}$, and the error vector $\mathbf{e}$ is generated exactly as in LWE. However, the coefficient matrix $\mathbf{A}$ in sparse LPN is chosen randomly from $\mathbb{Z}^{n\times m}_{p}$ so that each column has Hamming weight exactly $k$ for some small $k$. We study the problem in the regime where $k$ is a constant or polylogarithmic. The primary motivation for proposing this assumption is efficiency. Compared to LWE, the samples can be computed and stored with roughly $O(n/k)$ factor improvement in efficiency. Our results can be summarized as: Foundations: We show several properties of sparse LWE samples, including: 1) The hardness of LWE/LPN with dimension $k$ implies the hardness of sparse LWE/LPN with sparsity $k$ and arbitrary dimension $n \ge k$. 2) When the number of samples $m=\Omega(n \log p)$, length of the shortest vector of a lattice spanned by rows of a random sparse matrix is large, close to that of a random dense matrix of the same dimension (up to a small constant factor). 3) Trapdoors with small polynomial norm exist for random sparse matrices with dimension $n \times m = O(n \log p)$. 4) Efficient algorithms for sampling such matrices together with trapdoors exist when the dimension is $n \times m = \widetilde{\mathcal{O}}(n^2)$. Cryptanalysis: We examine the suite of algorithms that have been used to break LWE and sparse LPN. While naively many of the attacks that apply to LWE do not exploit sparsity, we consider natural extensions that make use of sparsity. We propose a model to capture all these attacks. Using this model we suggest heuristics on how to identify concrete parameters. Our initial cryptanalysis suggests that concretely sparse LWE with a modest $k$ and slightly bigger dimension than LWE will satisfy similar level of security as LWE with similar parameters. Applications: We show that the hardness of sparse LWE implies very efficient homomorphic encryption schemes for low degree computations. We obtain the first secret key Linearly Homomorphic Encryption (LHE) schemes with slightly super-constant, or even constant, overhead, which further has applications to private information retrieval, private set intersection, etc. We also obtain secret key homomorphic encryption for arbitrary constant-degree polynomials with slightly super-constant, or constant, overhead. We stress that our results are preliminary. However, our results make a strong case for further investigation of sparse LWE.

We show that the outsourcing algorithm for the case of linear constraints [IEEE Trans. Cloud Comput., 2023, 11(1), 484-498] cannot keep output privacy, due to the simple translation transformation. We also suggest a remedy method by adopting a hybrid transformation which combines the usual translation transformation and resizing transformation so as to protect the output privacy.

Creating an adversary resilient construction of the Learned Bloom Filter with provable guarantees is an open problem. We define a strong adversarial model for the Learned Bloom Filter. Our adversarial model extends an existing adversarial model designed for the Classical (i.e not ``Learned'') Bloom Filter by prior work and considers computationally bounded adversaries that run in probabilistic polynomial time (PPT). Using our model, we construct an adversary resilient variant of the Learned Bloom Filter called the Downtown Bodega Filter. We show that: if pseudo-random permutations exist, then an Adversary Resilient Learned Bloom Filter may be constructed with $2\lambda$ extra bits of memory and at most one extra pseudo-random permutation in the critical path. We construct a hybrid adversarial model for the case where a fraction of the query workload is chosen by an adversary. We show realistic scenarios where using the Downtown Bodega Filter gives better performance guarantees compared to alternative approaches in this hybrid model.

This paper presents a Generalized BFV (GBFV) fully homomorphic encryption scheme that encrypts plaintext spaces of the form $\mathbb{Z}[x]/(\Phi_m(x), t(x))$ with $\Phi_m(x)$ the $m$-th cyclotomic polynomial and $t(x)$ an arbitrary polynomial. GBFV encompasses both BFV where $t(x) = p$ is a constant, and the CLPX scheme (CT-RSA 2018) where $m = 2^k$ and $t(x) = x-b$ is a linear polynomial. The latter can encrypt a single huge integer modulo $\Phi_m(b)$, has much lower noise growth than BFV (linear in $m$ instead of exponential), but cannot be bootstrapped. We show that by a clever choice of $m$ and higher degree polynomial $t(x)$, our scheme combines the SIMD capabilities of BFV with the low noise growth of CLPX, whilst still being efficiently bootstrappable. Moreover, we present parameter families that natively accommodate packed plaintext spaces defined by a large cyclotomic prime, such as the Fermat prime $\Phi_2(2^{16}) = 2^{16} + 1$ and the Goldilocks prime $\Phi_6(2^{32}) = 2^{64} - 2^{32} + 1$. These primes are often used in homomorphic encryption applications and zero-knowledge proof systems. Due to the lower noise growth, e.g. for the Goldilocks prime, GBFV can evaluate circuits whose multiplicative depth is more than $5$ times larger than native BFV. As a result, we can evaluate either larger circuits or work with much smaller ring dimensions. In particular, we can natively bootstrap GBFV at 128-bit security for a large prime, already at ring dimension $2^{14}$, which was impossible before. We implemented the GBFV scheme on top of the SEAL library and achieve a latency of only $5$ seconds to bootstrap a ciphertext encrypting $4096$ elements modulo $2^{16}+1$.

Tweakable enciphering modes (TEMs) provide security in a variety of storage and space-critical applications like disk and file-based encryption, and packet-based communication protocols, among others. XCB-AES (known as XCBv2) is specified in the IEEE 1619.2 standard for encryption of sector-oriented storage media and it comes with a proof of security for block-aligned input messages. In this work, we demonstrate an attack on XCBv2. We show that XCBv2 is $\textit{insecure}$ also for full block messages by presenting a $\textit{partial}$ plaintext recovery attack using $\textit{only}$ two queries. We demonstrate that our attack further applies to the HCI and MXCB TEMs, which follow a similar design approach to XCBv2. Following the responsible disclosure process, we communicated the attack details to IEEE and the authors of XCB-AES. The authors have confirmed the validity of our attack on 02/09/2024. In a recent work, Wang et al. also presented stronger attacks on all XCB variants that can recover $\textit{full}$ plaintext and proposed a fixed variant called XCB*. We highlight that our attack is not applicable on XCB*. Our next contribution is to strengthen the provable security of XCB* (currently $n/3$ bits in queried blocks). We propose a new modular TEM called GEM which can be seen as a generalization of the Hash-CTR-Hash approach as used in XCB-style and HCTR-style TEMs. We are able to prove that GEM achieves full $n$-bit security using $\textit{only}$ $n$-bit PRP/PRF. We also give two concrete GEM instantiations: $\mathsf{KohiNoor}$ and $\mathsf{DaryaiNoor}$, both of which are based on AES-128 and GHASH-256, and internally use variants of the CTR-based weak pseudorandom functions GCTR-3 and SoCTR, respectively. SoCTR uses AES-128 and GCTR-3 is based on $\mathsf{ButterKnife}$-256. Our security proofs show that both $\mathsf{KohiNoor}$ and $\mathsf{DaryaiNoor}$ provide full $n$-bit security. From applications perspective, $\mathsf{DaryaiNoor}$ addresses the need for reusing classical components, while $\mathsf{KohiNoor}$ enhances performance by leveraging a more modern primitive based on the AES/Deoxys round function. Our implementation demonstrate competitive performance: For typical 4KiB sector size, $\mathsf{KohiNoor}$'s performance is on par with AES\textsubscript{6}-CTET+, yet achieving higher standard security guarantees. $\mathsf{DaryaiNoor}$ is on par with AES-CTET+ performance-wise while also maintaining higher security with standard components. Our GEM instances triple the security margin of XCB* and double that of HCTR2 at the cost of performance loss of only 12\% ($\mathsf{KohiNoor}$) and 68\% ($\mathsf{DaryaiNoor}$) for 4KiB messages.

We introduce WHIR, a new IOP of proximity that offers small query complexity and exceptionally fast verification time. The WHIR verifier typically runs in a few hundred microseconds, whereas other verifiers in the literature require several milliseconds (if not much more). This significantly improves the state of the art in verifier time for hash-based SNARGs (and beyond). Crucially, WHIR is an IOP of proximity for constrained Reed–Solomon codes, which can express a rich class of queries to multilinear polynomials and to univariate polynomials. In particular, WHIR serves as a direct replacement for protocols like FRI, STIR, BaseFold, and others. Leveraging the rich queries supported by WHIR and a new compiler for multilinear polynomial IOPs, we obtain a highly efficient SNARG for generalized R1CS. As a comparison point, our techniques also yield state-of-the-art constructions of hash-based (non-interactive) polynomial commitment schemes for both univariate and multivariate polynomials (since sumcheck queries naturally express polynomial evaluations). For example, if we use WHIR to construct a polynomial commitment scheme for degree 222, with 100 bits of security, then the time to commit and open is 1.2 seconds, the sender communicates 63 KiB to the receiver, and the opening verification time is 360 microseconds.

The implementation of cryptographic algorithms must be protected against physical attacks. Side-channel and fault injection analyses are two prominent such implem\-entation-level attacks. Protections against either do exist; they are characterized by security orders: the higher the order, the more difficult the attack. In this paper, we leverage fast discrete Fourier transform to reduce the complexity of high-order masking, and extend it to allow for fault detection and/or correction. The security paradigm is that of code-based masking. Coding theory is amenable both to mix the information and masking material at a prescribed order, and to detect and/or correct errors purposely injected by an attacker. For the first time, we show that quasi-linear masking (pioneered by Goudarzi, Joux and Rivain at ASIACRYPT 2018) can be achieved alongside with cost amortisation. This technique consists in masking several symbols/bytes with the same masking material, therefore improving the efficiency of the masking. Similarly, it allows to optimize the detection capability of codes as linear codes are all the more efficient as the information to protect is longer. Namely, we prove mathematically that our scheme features side-channel security order of $d+1-t$, detects $d$ faults and corrects $\lfloor(d-1)/2\rfloor$ faults, where $2d+1$ is the encoding length and $t$ is the information size ($t\geq1$). Applied to AES, one can get side-channel protection of order $d=7$ when masking one column/line ($t=4$ bytes) at once. In addition to the theory, that makes use of the Frobenius Additive Fast Fourier Transform, we show performance results, both in software and hardware.

Let $(N,e)$ be a public key of the RSA cryptosystem, and $d$ be the corresponding private key. In practice, we usually choose a small $e$ for quick encryption. In this paper, we improve partial private key exposure attacks against RSA with MSBs of $d$ and small $e$. The key idea is that under such a setting we can usually obtain more information about the prime factors of $N$ and then, by solving a univariate modular polynomial equation using Coppersmith's method, $N$ can be factored in polynomial time. Compared to previous results, we reduce the number of the leaked bits in $d$ that are needed to mount the attack by $\log_2 (e)$ bits. For $e=65537$, previous work required an additional enumeration of 17 bits to achieve our new bound, resulting in a $2^{10}$ (or 1,024) x increase in time consumption. Furthermore, our experiments show that for a $1024$-bit modulus $N$, our attack can achieve the theoretical bound on a simple personal computer, which verifies the new method.

We construct a quantum money/quantum lightning scheme from class group actions on elliptic curves over $F_{p}$. Our scheme, which is based on the invariant money construction of Liu-Montgomery-Zhandry (Eurocrypt '23), is simple to describe. We believe it to be the most instantiable and well-defined quantum money construction known so far. The security of our quantum lightning construction is exactly equivalent to the (conjectured) hardness of constructing two uniform superpositions over elliptic curves in an isogeny class which is acted on simply transitively by an exponentially large ideal class group. However, we needed to advance the state of the art of isogenies in order to achieve our scheme. In partcular, we show: 1. An efficient (quantum) algorithm for sampling a uniform superposition over a cryptographically large isogeny class. 2. A method for specifying polynomially many generators for the class group so that polynomial-sized products yield an exponential-sized subset of class group, modulo a seemingly very modest assumption. Achieving these results also requires us to advance the state of the art of the (pure) mathematics of elliptic curves, and we are optimistic that the mathematical tools we developed in this paper can be used to advance isogeny-based cryptography in other ways.

We develop and implement AlgoROM, a tool to systematically analyze the security of a wide class of symmetric primitives in idealized models of computation. The schemes that we consider are those that can be expressed over an alphabet consisting of XOR and function symbols for hash functions, permutations, or block ciphers. We implement our framework in OCaml and apply it to a number of prominent constructions, which include the Luby–Rackoff (LR), key-alternating Feistel (KAF), and iterated Even–Mansour (EM) ciphers, as well as substitution-permutation networks (SPN). The security models we consider are (S)PRP, and strengthenings thereof under related-key (RK), key-dependent message (KD), and more generally key-correlated (KC) attacks. Using AlgoROM, we are able to reconfirm a number of classical and previously established security theorems, and in one case we identify a gap in a proof from the literature (Connolly et al., ToSC'19). However, most results that we prove with AlgoROM are new. In particular, we obtain new positive results for LR, KAF, EM, and SPN in the above models. Our results better reflect the configurations actually implemented in practice, as they use a single idealized primitive. In contrast to many existing tools, our automated proofs do not operate in symbolic models, but rather in the standard probabilistic model for cryptography.

XCB, a tweakable enciphering mode, is part of IEEE Std. 1619.2 for shared storage media. We show that all versions of XCB are not secure through three plaintext recovery attacks. A key observation is that XCB behaves like an LRW1-type tweakable block cipher for single-block messages, which lacks CCA security. The first attack targets one-block XCB, using three queries to recover the plaintext. The second one requires four queries to recover the plaintext that excludes one block. The last one requires seven queries to recover the full plaintext. The first attack applies to any scheme that follows the XCB structure, whereas the latter two attacks work on all versions of XCB, exploiting the separable property of the underlying universal hash function. We also discuss the impact of these vulnerabilities on XCB-based applications, such as disk encryption, nonce-based encryption, deterministic authenticated encryption and robust authenticated encryption, highlighting the risks due to XCB's failure to achieve STPRP security. To address these flaws, we propose the XCB* structure, an improved version of XCB that adds only two XOR operations. We prove that XCB* is STPRP-secure when using AXU hash functions, SPRPs, and a secure IV-based stream cipher.

In spite of being a popular technique for designing block ciphers, Lai-Massey networks have received considerably less attention from a security analysis point-of-view than Feistel networks and Substitution-Permutation networks. In this paper we study the beyond-birthday-bound (BBB) security of Lai-Massey networks with independent random round functions against chosen-plaintext adversaries. Concretely, we show that five rounds are necessary and sufficient to achieve BBB security.

Oblivious Transfer (OT) is one of the fundamental building blocks in cryptography that enables various privacy-preserving applications. Constructing efficient OT schemes has been an active research area. This paper presents three efficient two-round pairing-free k-out-of-N oblivious transfer protocols with standard security. Our constructions follow the minimal communication pattern: the receiver sends k messages to the sender, who responds with n+k messages, achieving the lowest data transmission among pairing-free k-out-of-n OT schemes. Furthermore, our protocols support adaptivity and also, enable the sender to encrypt the n messages offline, independent of the receiver's variables, offering significant performance advantages in one-sender-multiple-receiver scenarios. We provide security proofs under the Computational Diffie-Hellman (CDH) and RSA assumptions, without relying on the Random Oracle Model. Our protocols combine minimal communication rounds, adaptivity, offline encryption capability, and provable security, making them well-suited for privacy-preserving applications requiring efficient oblivious transfer. Furthermore, the first two proposed schemes require only one operation, making them ideal for resource-constrained devices.

Homomorphic encryption has long been used to build voting schemes. Additively homomorphic encryption only allows simple count- ing functions. Lattice-based fully (or somewhat) homomorphic encryp- tion allows more general counting functions, but the required parameters quickly become impractical if used naively. It is safe to leak information during the counting function evaluation, as long as the information could be derived from the public result. To exploit this observation, we de- sign a flexible framework for using somewhat homomorphic encryption for voting that incorporates random input and allows controlled leakage of information. We instantiate the framework using novel circuits with low but significant multiplicative depth exploiting the fact that, in the context of voting, leakage of certain information during homomorphic evaluation can be permitted. We also instantiate the framework with a circuit that uses random input to shuffle without the use of mixnets.

We study differential additions formulas on Kummer lines that factorize through a degree $2$ isogeny $\phi$. We call the resulting formulas half differential additions: from the knowledge of $\phi(P), \phi(Q)$ and $P-Q$, the half differential addition allows to recover $P+Q$. We explain how Mumford's theta group theory allows, in any model of Kummer lines, to find a basis of the half differential relations. This involves studying the dimension $2$ isogeny $(P, Q) \mapsto (P+Q, P-Q)$. We then use the half differential addition formulas to build a new type of Montgomery ladder, called the half-ladder, using a time-memory trade-off. On a Montgomery curve with full rational $2$-torsion, our half ladder first build a succession of isogeny images $P_i=\phi_i(P_{i-1})$, which only depends on the base point $P$ and not the scalar $n$, for a pre-computation cost of $2S+1m_0$ by bit. Then we use half doublings and half differential additions to compute any scalar multiplication $n \cdot P$, for a cost of $4M+2S+1m_0$ by bit. The total cost is then $4M+4S+2m_0$, even when the base point $P$ is not normalized. By contrast, the usual Montgomery ladder costs $4M+4S+1m+1m_0$ by bit, for a normalized point. In the appendix, we extend our approach to higher dimensional ladders in theta coordinates.

We present $\mathsf{Protoss}$, a new balanced PAKE protocol with optimal communication efficiency. Messages are only 160 bits long and the computational complexity is lower than all previous approaches. Our protocol is proven secure in the random oracle model and features a security proof in a strong security model with multiple parties and multiple sessions, while allowing for generous attack queries including multiple $\mathsf{Test}$-queries. Moreover, the proof is in the practically relevant single-bit model (that is harder to achieve than the multiple-bit model) and tightly reduces to the Strong Square Diffie-Hellman assumption (SSQRDH). This allows for very efficient, theoretically-sound instantiations and tight compositions with symmetric primitives.

The hardness of Kolmogorov complexity is intricately connected to the existence of one-way functions and derandomization. An important and elegant notion is Levin's version of Kolmogorov complexity, \(\mathsf{Kt}\), and its decisional variant, \(\mathsf{MKtP}\). The question whether \(\mathsf{MKtP}\) can be computed in polynomial time is particularly interesting because it is not subject to known technical barriers such as algebrization or natural proofs that would explain the lack of a proof for \(\mathsf{MKtP} \not\in \mathsf{P}\). We take a major step towards proving \(\mathsf{MKtP} \not\in \mathsf{P}\) by developing a novel yet simple diagonalization technique to show unconditionally that \(\mathsf{MKtP} \not \in \mathsf{DTIME}[O(n)]\), i.e., no deterministic linear-time algorithm can solve \(\mathsf{MKtP}\) on every instance. This allows us to affirm a conjecture by Ren and Santhanam [STACS:RS22] about a non-halting variant of \(\mathsf{Kt}\) complexity. Additionally, we give conditional lower bounds for \(\mathsf{MKtP}\) that tolerate either more runtime or one-sided error. If the underlying computational model has a linear-time universal simulation, e.g.\ random-access machines, then we obtain a quadratic lower bound, i.e., \(\mathsf{MKtP} \not\in \mathsf{DTIME}[O(n^2)]\).

Deep neural networks (DNNs) are valuable assets, yet their public accessibility raises security concerns about parameter extraction by malicious actors. Recent work by Carlini et al. (Crypto’20) and Canales- Martínez et al. (Eurocrypt’24) has drawn parallels between this issue and block cipher key extraction via chosen plaintext attacks. Leveraging differential cryptanalysis, they demonstrated that all the weights and biases of black-box ReLU-based DNNs could be inferred using a polynomial number of queries and computational time. However, their attacks relied on the availability of the exact numeric value of output logits, which allowed the calculation of their derivatives. To overcome this limitation, Chen et al. (Asiacrypt’24) tackled the more realistic hard-label scenario, where only the final classification label (e.g., "dog" or "car") is accessible to the attacker. They proposed an extraction method requiring a polynomial number of queries but an exponential execution time. In addition, their approach was applicable only to a restricted set of architectures, could deal only with binary classifiers, and was demonstrated only on tiny neural networks with up to four neurons split among up to two hidden layers. This paper introduces new techniques that, for the first time, achieve cryptanalytic extraction of DNN parameters in the most challenging hard-label setting, using both a polynomial number of queries and polynomial time. We validate our approach by extracting nearly one million parameters from a DNN trained on the CIFAR-10 dataset, comprising 832 neurons in four hidden layers. Our results reveal the surprising fact that all the weights of a ReLU-based DNN can be efficiently determined by analyzing only the geometric shape of its decision boundaries.

In modern business to customer interactions, handling private or confidential data is essential. Private Function Evaluation (PFE) protocols ensure the privacy of both the customers' input data and the business' function evaluated on it which is often sensitive intellectual property (IP). However, fully hiding the function in PFE results in high performance overhead. Semi-Private Function Evaluation (SPFE) is a generalization of PFE to only partially hide the function, whereas specific non-critical components remain public. Our paper introduces a novel framework designed to make SPFE accessible to non-experts and practical for real-world deployments. To achieve this, we improve on previous SPFE solutions in two aspects. First, we enhance the developer experience by leveraging High-Level Synthesis (HLS), making our tool more user-friendly than previous SPFE frameworks. Second, we achieve a \(2 \times\) speedup compared to the previous state-of-the-art through more efficient underlying constructions and the usage of Lookup Tables (LUTs). We evaluate the performance of our framework in terms of communication and runtime efficiency. Our final implementation is available as an open-source project, aiming to bridge the gap between advanced cryptographic protocols and their practical application in industry scenarios.

We revisit the problem of Authorized Private Set Intersection (APSI), which allows mutually untrusting parties to authorize their items using a trusted third-party judge before privately computing the intersection. We also initiate the study of Partial-APSI, a novel privacy-preserving generalization of APSI in which the client only reveals a subset of their items to a third-party semi-honest judge for authorization. Partial-APSI allows for partial verification of the set, preserving the privacy of the party whose items are being verified. Both APSI and Partial-APSI have a number of applications, including genome matching, ad conversion, and compliance with privacy policies such as the GDPR. We present two protocols based on bilinear pairings with linear communication. The first realizes the APSI functionality, is secure against a malicious client, and requires only one round of communication during the online phase. Our second protocol realizes the Partial-APSI functionality and is secure against a client that may maliciously inject elements into its input set, but who follows the protocol semi-honestly otherwise. We formally prove correctness and security of these protocols and provide an experimental evaluation to demonstrate their practicality. Our protocols can be efficiently run on commodity hardware. We also show that our protocols are massively parallelizable by running our experiments on a compute grid across 50 cores.

We show that we can break SIDH in classical polynomial time, even with a random starting curve $E_0$.

We survey different (efficient or not) representations of isogenies, with a particular focus on the recent "higher dimensional" isogeny representation, and algorithms to manipulate them.

In quantum cryptography, there could be a new world, Microcrypt, where cryptography is possible but one-way functions (OWFs) do not exist. Although many fundamental primitives and useful applications have been found in Microcrypt, they lack ``OWFs-free'' concrete hardness assumptions on which they are based. In classical cryptography, many hardness assumptions on concrete mathematical problems have been introduced, such as the discrete logarithm (DL) problems or the decisional Diffie-Hellman (DDH) problems on concrete group structures related to finite fields or elliptic curves. They are then abstracted to generic hardness assumptions such as the DL and DDH assumptions over group actions. Finally, based on these generic assumptions, primitives and applications are constructed. The goal of the present paper is to introduce several abstracted generic hardness assumptions in Microcrypt, which could connect the concrete mathematical hardness assumptions with applications. Our assumptions are based on a quantum analogue of group actions. A group action is a tuple $(G,S,\star)$ of a group $G$, a set $S$, and an operation $\star:G\times S\to S$. We introduce a quantum analogue of group actions, which we call quantum group actions (QGAs), where $G$ is a set of unitary operators, $S$ is a set of states, and $\star$ is the application of a unitary on a state. By endowing QGAs with some reasonable hardness assumptions, we introduce a natural quantum analogue of the decisional Diffie-Hellman (DDH) assumption and pseudorandom group actions. Based on these assumptions, we construct classical-query pseudorandom function-like state generators (PRFSGs). PRFSGs are a quantum analogue of pseudorandom functions (PRFs), and have many applications such as IND-CPA SKE, EUF-CMA MAC, and private-key quantum money schemes. Because classical group actions are instantiated with many concrete mathematical hardness assumptions, our QGAs could also have some concrete (even OWFs-free) instantiations.

Although one-way functions are well-established as the minimal primitive for classical cryptography, a minimal primitive for quantum cryptography is still unclear. Universal extrapolation, first considered by Impagliazzo and Levin (1990), is hard if and only if one-way functions exist. Towards better understanding minimal assumptions for quantum cryptography, we study the quantum analogues of the universal extrapolation task. Specifically, we put forth the classical$\rightarrow$quantum extrapolation task, where we ask to extrapolate the rest of a bipartite pure state given the first register measured in the computational basis. We then use it as a key component to establish new connections in quantum cryptography: (a) quantum commitments exist if classical$\rightarrow$quantum extrapolation is hard; and (b) classical$\rightarrow$quantum extrapolation is hard if any of the following cryptographic primitives exists: quantum public-key cryptography (such as quantum money and signatures) with a classical public key or 2-message quantum key distribution protocols. For future work, we further generalize the extrapolation task and propose a fully quantum analogue. We show that it is hard if quantum commitments exist, and it is easy for quantum polynomial space.

The classical distributed key generation protocols (DKG) are resurging due to their widespread applications in blockchain. While efforts have been made to improve DKG communication, practical large-scale deployments are still yet to come due to various challenges, including the heavy computation and communication (particularly broadcast) overhead in their adversarial cases. In this paper, we propose a practical DKG for DLog-based cryptosystems, which achieves (quasi-)linear computation and communication per-node cost with the help of a common coin, even in the face of the maximal amount of Byzantine nodes. Moreover, our protocol is secure against adaptive adversaries, which can corrupt less than half of all nodes. The key to our improvements lies in delegating the most costly operations to an Any-Trust group together with a set of techniques for adaptive security. This group is randomly sampled and consists of a small number of individuals. The population only trusts that at least one member in the group is honest, without knowing which one. Moreover, we present a generic transformer that enables us to efficiently deploy a conventional distributed protocol like our DKG, even when the participants have different weights. Additionally, we introduce an extended broadcast channel based on a blockchain and data dispersal network (such as IPFS), enabling reliable broadcasting of arbitrary-size messages at the cost of constant-size blockchain storage. Our DKG leads to a fully practical instantiation of Filecoin's checkpointing mechanism, in which all validators of a Proof-of-Stake (PoS) blockchain periodically run DKG and threshold signing to create checkpoints on Bitcoin, to enhance the security of the PoS chain. In comparison with the recent checkpointing approach of Babylon (Oakland, 2023), ours enjoys a significantly smaller cost of Bitcoin transaction fees. For $2^{12}$ validators, our cost is merely 0.4\% of that incurred by Babylon's approach.

In the multi-user with corruptions (muc) setting there are $n\geq 1$ users, and the goal is to prove that, even in the face of an adversary that adaptively corrupts users to expose their keys, un-corrupted users retain security. This can be considered for many primitives including signatures and encryption. Proofs of muc security, while possible, generally suffer a factor n loss in tightness, which can be large. This paper gives new proofs where this factor is reduced to the number c of corruptions, which in practice is much smaller than n. We refer to this as corruption-parametrized muc (cp-muc) security. We give a general result showing it for a class of games that we call local. We apply this to get cp-muc security for signature schemes (including ones in standards and in TLS 1.3) and some forms of public-key and symmetric encryption. Then we give dedicated cp-muc security proofs for some important schemes whose underlying games are not local, including the Hashed ElGamal and Fujisaki-Okamoto KEMs and authenticated key exchange. Finally, we give negative results to show optimality of our bounds.

We examine the problem of finding small solutions to systems of modular multivariate polynomials. While the case of univariate polynomials has been well understood since Coppersmith's original 1996 work, multivariate systems typically rely on carefully crafted shift polynomials and significant manual analysis of the resulting Coppersmith lattice. In this work, we develop several algorithms that make such hand-crafted strategies obsolete. We first use the theory of Gröbner bases to develop an algorithm that provably computes an optimal set of shift polynomials, and we use lattice theory to construct a lattice which provably contains all desired short vectors. While this strategy is usable in practice, the resulting lattice often has large rank. Next, we propose a heuristic strategy based on graph optimization algorithms that quickly identifies low-rank alternatives. Third, we develop a strategy which symbolically precomputes shift polynomials, and we use the theory of polytopes to polynomially bound the running time. Like Meers and Nowakowski's automated method, our precomputation strategy enables heuristically and automatically determining asymptotic bounds. We evaluate our new strategies on over a dozen previously studied Coppersmith problems. In all cases, our unified approach achieves the same recovery bounds in practice as prior work, even improving the practical bounds for four of the problems. In four problems, we find smaller and more efficient lattice constructions, and in two problems, we improve the existing asymptotic bounds. While our strategies are still heuristic, they are simple to describe, implement, and execute, and we hope that they drastically simplify the application of Coppersmith's method to systems of multivariate polynomials.

Value Added Tax (VAT) is a cornerstone of government rev- enue systems worldwide, yet its self-reported nature has historically been vulnerable to fraud. While transaction-level reporting requirements may tackle fraud, they raise concerns regarding data security and overreliance on tax authorities as fully trusted intermediaries. To address these issues, we propose Verifiable VAT, a protocol that enables confidential and verifiable VAT reporting. Our system allows companies to confidentially report VAT as a homomorphic commitment in a centrally managed permissioned ledger, using zero-knowledge proofs to provide integrity guarantees. We demonstrate that the scheme strictly limits the amount of fraud possible due to misreporting. Additionally, we introduce a scheme so companies can (dis)prove exchange of VAT with fraudulent companies. The proposed protocol is flexible with regards to real-world jurisdictions’ requirements, and underscores the potential of cryptographic methods to enhance the integrity and confidentiality of tax systems.

Shared randomness in blockchain can expand its support for randomized applications and can also help strengthen its security. Many existing blockchains rely on external randomness beacons for shared randomness, but this approach reduces fault tolerance, increases latency, and complicates application development. An alternate approach is to let the blockchain validators generate fresh shared randomness themselves once for every block. We refer to such a design as the \emph{on-chain} randomness. In this paper, we design an efficient on-chain randomness protocol for Byzantine fault-tolerance based Proof-of-Stake blockchains with weighted validators. A key component of our protocol is a weighted verifiable unpredictable function (VUF). The notable feature of our weighted VUF is that the computation and communication costs of parties are independent of their weight. This is crucial for scalability of on-chain randomness where we repeatedly evaluate the weighted VUF in quick succession. We also design a new scalable publicly verifiable secret sharing~(PVSS) scheme with aggregatable transcript and use it to design a distributed key generation~(DKG) protocol for our VUF. We implemented our schemes on top of Aptos, a proof-of-stake blockchain deployed in production, conducted an end-to-end evaluation with 112 validators and a total weight of up to 4053. In this setup, our on-chain randomness protocol adds only 133 milliseconds of latency compared to a protocol without randomness. We also demonstrate the performance improvements of our design through rigorous comparison with baseline methods.

In this paper we study several computational problems related to current post-quantum cryptosystems based on isogenies between supersingular elliptic curves. In particular we prove that the supersingular isogeny path and endomorphism ring problems are unconditionally equivalent under polynomial time reductions. We show that access to a factoring oracle is sufficient to solve the Quaternion path problem of KLPT and prove that these problems are equivalent, where previous results either assumed heuristics or the generalised Riemann Hypothesis (GRH). Consequently, given Shor’s quantum algorithm for factorisation, our results yield unconditional quantum polynomial reductions between the isogeny path and EndRing problems. Recently these reductions have become foundational for the security of isogeny-based cryptography

Randomized distributed function computation refers to remote function computation where transmitters send data to receivers which compute function outputs that are randomized functions of the inputs. We study the applications of semantic communications in randomized distributed function computation to illustrate significant reductions in the communication load, with a particular focus on privacy. The semantic communication framework leverages generalized remote source coding methods, where the remote source is a randomized version of the observed data. Since satisfying security and privacy constraints generally require a randomization step, semantic communication methods can be applied to such function computation problems, where the goal is to remotely simulate a sequence at the receiver such that the transmitter and receiver sequences follow a target probability distribution. Our performance metrics guarantee (local differential) privacy for each input sequence, used in two different distributed function computation problems, which is possible by using strong coordination methods. This work provides lower bounds on Wyner's common information (WCI), which is one of the two corner points of the coordination-randomness rate region characterizing the ultimate limits of randomized distributed function computation. The WCI corresponds to the case when there is no common randomness shared by the transmitter and receiver. Moreover, numerical methods are proposed to compute the other corner point for continuous-valued random variables, for which an unlimited amount of common randomness is available. Results for two problems of practical interest illustrate that leveraging common randomness can decrease the communication load as compared to the WCI corner point significantly. We also illustrate that semantic communication gains over lossless compression methods are achieved also without common randomness, motivating further research on limited common randomness scenarios.

We propose a new cryptographic primitive called ``selective batched identity-based encryption'' (Selective Batched IBE) and its thresholdized version. The new primitive allows encrypting messages with specific identities and batch labels, where the latter can represent, for example, a block number on a blockchain. Given an arbitrary subset of identities for a particular batch, our primitive enables efficient issuance of a single decryption key that can be used to decrypt all ciphertexts having identities that are included in the subset while preserving the privacy of all ciphertexts having identities that are excluded from the subset. At the heart of our construction is a new technique that enables public aggregation (i.e. without knowledge of any secrets) of any subset of identities, into a succinct digest. This digest is used to derive, via a master secret key, a single succinct decryption key for all the identities that were digested in this batch. In a threshold system, where the master key is distributed as secret shares among multiple authorities, our method significantly reduces the communication (and in some cases, computation) overhead for the authorities. It achieves this by making their costs for key issuance independent of the batch size. We present a concrete instantiation of a Selective Batched IBE scheme based on the KZG polynomial commitment scheme by Kate et al. (Asiacrypt'10) and a modified form of the BLS signature scheme by Boneh et al. (Asiacrypt'01). The construction is proven secure in the generic group model (GGM). In a blockchain setting, the new construction can be used for achieving mempool privacy by encrypting transactions to a block, opening only the transactions included in a given block and hiding the transactions that are not included in it. With the thresholdized version, multiple authorities (validators) can collaboratively manage the decryption process. Other possible applications include scalable support via blockchain for fairness of dishonest majority MPC, and conditional batched threshold decryption that can be used for implementing secure Dutch auctions and privacy preserving options trading.

Non-interactive zero-knowledge (NIZK) proofs allow a prover to convince a verifier about the validity of an NP-statement by sending a single message and without disclosing any additional information (besides the validity of the statement). Single-message cryptographic proofs are very versatile, which has made them widely used both in theory and in practice. This is particularly true for succinct proofs, where the length of the message is sublinear in the size of the NP relation. This versatility, unfortunately, comes at a price, since any NIZK proof system requires some form of setup, like a common reference string. One way to circumvent the need for a setup is by relying on a Random Oracle. Unfortunately, if the Random Oracle is modeled as a Global resource that the simulator is not allowed to program, then it is impossible to obtain a secure NIZK. This impossibility has been circumvented by allowing the simulator (and the real-world adversary) to program the RO, and allowing the honest parties to check, via a special interface, if the RO outputs have been programmed. In this work, we show that this impossibility can be circumvented by meaningfully weakening the Universal Composability framework following the model proposed by Broadnax et al. (Eurocrypt 2017). In this model, the ideal world functionalities are allowed to interact with oracles that have quasi-polynomial time capabilities. As our main result, we propose the first composable NIZK proof system that relies on a global (non-programmable) random oracle as its only form of setup. The NIZK scheme we propose is witness-succinct (with proofs logarithmic in the size of the witness). Our results break both the barrier of programmability of the random oracle and of polylogarithmic proof size for UC-secure NIZKs with transparent setups. We are able to construct our NIZK using the framework proposed by Ganesh et al. (Eurocrypt 2023), which requires—among other building blocks—a polynomial commitment scheme with special features and a polynomial encoding scheme (a primitive that appropriately masks a witness as a polynomial). As a core technical contribution, we show a polynomial commitment of this type using a basic component of Bulletproofs as a building block, as well as a polynomial encoding based on techniques completely different from the ones from Ganesh et al..

The learning with errors problem (LWE) is one of the most important building blocks for post-quantum cryptography. To better understand the quantum hardness of LWE, it is crucial to explore quantum variants of LWE. To this end, Chen, Liu, and Zhandry [Eurocrypt 2022] defined S|LWE> and C|LWE> problems by encoding the error of LWE samples into quantum amplitudes, and showed efficient quantum algorithms for a few interesting amplitudes. However, algorithms or hardness results of the most interesting amplitude, Gaussian, were not addressed before. In this paper, we show new algorithms, hardness results and applications for S|LWE> and C|LWE> with real Gaussian, Gaussian with linear or quadratic phase terms, and other related amplitudes. Let n be the dimension of LWE samples. Our main results are 1. There is a $2^{\tilde{O}(\sqrt{n})}$-time algorithm for S|LWE> with Gaussian amplitude with known phase, given $2^{\tilde{O}(\sqrt{n})}$ many quantum samples. The algorithm is modified from Kuperberg's sieve, and in fact works for more general amplitudes as long as the amplitudes and phases are completely known. 2. There is a polynomial time quantum algorithm for solving S|LWE> and C|LWE> for Gaussian with quadratic phase amplitudes, where the sample complexity is as small as $\tilde{O}(n)$. As an application, we give a quantum oblivious LWE sampler where the core quantum sampler requires only quasi-linear sample complexity. This improves upon the previous oblivious LWE sampler given by Debris-Alazard, Fallahpour, Stehlé [STOC 2024], whose core quantum sampler requires $\tilde{O}(nr)$ sample complexity, where $r$ is the standard deviation of the error. 3. There exist polynomial time quantum reductions from standard LWE or worst-case GapSVP to S|LWE> with Gaussian amplitude with small unknown phase, and arbitrarily many samples. Compared to the first two items, the appearance of the unknown phase term places a barrier in designing efficient quantum algorithm for solving standard LWE via S|LWE>.

In this paper, we construct the first asymptotically efficient two-round $n$-out-of-$n$ and multi-signature schemes from lattices in the quantum random oracle model (QROM), using the Fiat-Shamir with Aborts (FSwA) paradigm. Our protocols can be viewed as the QROM~variants of the two-round protocols by Damgård et al. (JoC 2022). A notable feature of our protocol, compared to other counterparts in the classical random oracle model, is that each party performs an independent abort and still outputs a signature in exactly two rounds, making our schemes significantly more scalable. From a technical perspective, the simulation of QROM~and the efficient reduction from breaking underlying assumption to forging signatures are the essential challenges to achieving efficient QROM security for the previously related works. In order to conquer the former one we adopt the quantum-accessible pseudorandom function (QPRF) to simulate QROM. Particularly, we show that there exist a QPRF~which can be programmed and inverted, even against a quantum adversary. For the latter challenge, we tweak and apply the online extractability by Unruh (Eurocrypt 2015).

Provable privacy typically requires involved analysis and is often associated with unacceptable accuracy loss. While many empirical verification or approximation methods, such as Membership Inference Attacks (MIA) and Differential Privacy Auditing (DPA), have been proposed, these do not offer rigorous privacy guarantees. In this paper, we apply recently-proposed Probably Approximately Correct (PAC) Privacy to give formal, mechanized, simulation-based proofs for a range of practical, black-box algorithms: K-Means, Support Vector Machines (SVM), Principal Component Analysis (PCA) and Random Forests. To provide these proofs, we present a new simulation algorithm that efficiently determines anisotropic noise perturbation required for any given level of privacy. We provide a proof of correctness for this algorithm and demonstrate that anisotropic noise has substantive benefits over isotropic noise. Stable algorithms are easier to privatize, and we demonstrate privacy amplification resulting from introducing regularization in these algorithms; meaningful privacy guarantees are obtained with small losses in accuracy. We propose new techniques in order to reduce instability in algorithmic output and convert intractable geometric stability verification into efficient deterministic stability verification. Thorough experiments are included, and we validate our provable adversarial inference hardness against state-of-the-art empirical attacks.

In recent years quantum computing has developed rapidly. The security threat posed by quantum computing to cryptography makes it necessary to better evaluate the resource cost of attacking algorithms, some of which require quantum implementations of the attacked cryptographic building blocks. In this paper we manage to optimize quantum circuits of AES in several aspects. Firstly, based on de Brugière \textit{et al.}'s greedy algorithm, we propose an improved depth-oriented algorithm for synthesizing low-depth CNOT circuits with no ancilla qubits. Our algorithm finds a CNOT circuit of AES MixColumns with depth 10, which breaks a recent record of depth 16. In addition, our algorithm gives low-depth CNOT circuits for many MDS matrices and matrices used in block ciphers studied in related work. Secondly, we present a new structure named compressed pipeline structure to synthesize quantum circuits of AES, which can be used for constructing quantum oracles employed in quantum attacks based on Grover's and Simon's algorithms. When the number of ancilla qubits required by the round function and its inverse is not very large, our structure will have a better trade-off of $D$-$W$ cost. Moreover, our encryption oracle will have the lowest depth to date. We then give detailed encryption circuits of AES-128 under the guidance of our structure and make some comparisons with other circuits. Finally, the encryption part and the key schedule part have their own application scenarios. The Encryption oracle used in Simon's algorithm built with the former will have smaller round depth. For example, we can construct an AES-128 Encryption oracle with $T$-depth 33, while the previous best result is 60. A small variant of the latter, along with our method to make an Sbox input-invariant, can avoid the allocation of extra ancilla qubits for storing key words in the shallowed pipeline structure. Based on this, we achieve an encryption circuit of AES-128 with the lowest $TofD$-$W$ cost 130720 to date.

Artificial Intelligence (AI) has steadily improved across a wide range of tasks, and a significant breakthrough towards general intelligence was achieved with the rise of generative deep models, which have garnered worldwide attention. However, the development and deployment of AI are almost entirely controlled by a few powerful organizations and individuals who are racing to create Artificial General Intelligence (AGI). These centralized entities make decisions with little public oversight, shaping the future of humanity, often with unforeseen consequences. In this paper, we propose OML, which stands for Open, Monetizable, and Loyal AI, an approach designed to democratize AI development and shift control away from these monopolistic actors. OML is realized through an interdisciplinary framework spanning AI, blockchain, and cryptography. We present several ideas for constructing OML systems using technologies such as Trusted Execution Environments (TEE), traditional cryptographic primitives like fully homomorphic encryption and functional encryption, obfuscation, and AI-native solutions rooted in the sample complexity and intrinsic hardness of AI tasks. A key innovation of our work is the introduction of a new scientific field: AI-native cryptography, which leverages cryptographic primitives tailored to AI applications. Unlike conventional cryptography, which focuses on discrete data and binary security guarantees, AI-native cryptography exploits the continuous nature of AI data representations and their low-dimensional manifolds, focusing on improving approximate performance. One core idea is to transform AI attack methods, such as data poisoning, into security tools. This novel approach serves as a foundation for OML 1.0, an implemented system that demonstrates the practical viability of AI-native cryptographic techniques. At the heart of OML 1.0 is the concept of model fingerprinting, a novel AI-native cryptographic primitive that helps protect the integrity and ownership of AI models. The spirit of OML is to establish a decentralized, open, and transparent platform for AI development, enabling the community to contribute, monetize, and take ownership of AI models. By decentralizing control and ensuring transparency through blockchain technology, OML prevents the concentration of power and provides accountability in AI development that has not been possible before. To the best of our knowledge, this paper is the first to: • Identify the monopolization and lack of transparency challenges in AI deployment today and formulate the challenge as OML (Open, Monetizable, Loyal). • Provide an interdisciplinary approach to solving the OML challenge, incorporating ideas from AI, blockchain, and cryptography. • Introduce and formally define the new scientific field of AI-native cryptography. • Develop novel AI-native cryptographic primitives and implement them in OML 1.0, analyzing their security and effectiveness. • Leverage blockchain technology to host OML solutions, ensuring transparency, decentralization, and alignment with the goals of democratized AI development. Through OML, we aim to provide a decentralized framework for AI development that prioritizes open collaboration, ownership rights, and transparency, ultimately fostering a more inclusive AI ecosystem.

For primes $p$ with $p+1$ being smooth, the G-FFT from Li and Xing [LX23] is an algebraic FFT, which at first glance seems equivalent to the circle FFT from [IACR eprint 2024/278]: It also uses the circle curve over $\mathbb F_p$ (in other words the projective line) as underlying domain, and interpolates by low-degree functions with poles over the same set of points. However, their approach to control the degree of the FFT basis is fundamentally different. The G-FFT makes use of punctured Riemann-Roch spaces, and the construction works with the group doubling map only, no projection onto the $x$-axis involved. In this note we give an elementary description of the G-FFT without using abstract algebra. We describe a variant which uses a simpler, and in our opinion more natural function space, and which treats the exceptional point of the domain (the group identity) differently. In comparison to the circle FFT, the G-FFT (both the original as well as our variant) has the following downsides. Interpolation and domain evaluation costs the double number of multiplications (the twiddle is not an ``odd'' function), and the function space is not invariant under the group action, causing additional overhead when applied in STARKs.

We discuss zero-knowledge in the context of FRI-based STARKs using techniques desirable in practice: Randomization by polynomials over the basefield, and decomposing the overall quotient into polynomials of smaller degree.

Threshold variants of the Schnorr signature scheme have recently been at the center of attention due to their applications to cryptocurrencies. However, existing constructions for threshold Schnorr signatures among a set of $n$ parties with corruption threshold $t_c$ suffer from at least one of the following drawbacks: (i) security only against static (i.e., non-adaptive) adversaries, (ii) cubic or higher communication cost to generate a single signature, (iii) strong synchrony assumptions on the network, or (iv) $t_c+1$ are sufficient to generate a signature, i.e., the corruption threshold of the scheme equals its reconstruction threshold. Especially (iv) turns out to be a severe limitation for many asynchronous real-world applications where $t_c < n/3$ is necessary to maintain liveness, but a higher signing threshold of $n-t_c$ is needed. A recent scheme, ROAST, proposed by Ruffing et al. (ACM CCS 2022) addresses (iii) and (iv), but still falls short of obtaining subcubic communication complexity and adaptive security. In this work, we present HARTS, the first threshold Schnorr signature scheme to incorporate all these desiderata. More concretely: - HARTS is adaptively secure and remains fully secure and operational even under asynchronous network conditions in the presence of up to $t_c < n/3$ malicious parties. This is optimal. - HARTS outputs a Schnorr signature of size $\lambda$ with a near-optimal amortized communication cost of $O(\lambda n^2 \log{n})$ bits and a single asynchronous online round per signature. - HARTS is high-threshold: no fewer than $t_r+1$ signature shares can be combined to yield a full signature, where any $t_r\in [t_c,n-t_c)$ is supported. This especially covers the case $t_r \geq 2n/3 > 2t_c$. This is optimal. We prove our result in a modular fashion in the algebraic group model. At the core of our construction, we design a new simple and adaptively secure high-threshold asynchronous verifiable secret sharing (AVSS) scheme which may be of independent interest.

We introduce an efficient SNARK for towers of binary fields. Adapting Brakedown (CRYPTO '23), we construct a multilinear polynomial commitment scheme suitable for polynomials over tiny fields, including that with just two elements. Our commitment scheme, unlike those of previous works, treats small-field polynomials with no embedding overhead. We further introduce binary-field adaptations of HyperPlonk (EUROCRYPT '23)'s product and permutation checks and of Lasso ('23)'s lookup. Our binary PLONKish variant captures standard hash functions—like Keccak-256 and Grøstl—extremely efficiently. With recourse to thorough performance benchmarks, we argue that our scheme can efficiently generate precisely those Keccak-256-proofs which critically underlie modern efforts to scale Ethereum.

As an emerging primitive, Registered Functional Encryption (RFE) eliminates the key-escrow issue that threatens numerous works for functional encryption, by replacing the trusted authority with a transparent key curator and allowing each user to sample their decryption keys locally. In this work, we present a new black-box approach to construct RFE for all polynomial-sized circuits. It considers adaptive simulation-based security in the bounded collusion model (Gorbunov et al. - CRYPTO'12), where the security can be ensured only if there are no more than Q >= 1 corrupted users and $Q$ is fixed at the setup phase. Unlike earlier works, we do not employ unpractical Indistinguishability Obfuscation (iO). Conversely, it can be extended to support unbounded users, which is previously only known from iO. Technically, our general compiler exploits garbled circuits and a novel variant of slotted Registered Broadcast Encryption (RBE), namely global slotted RBE. This primitive is similar to slotted RBE, but needs optimally compact public parameters and ciphertext, so as to satisfy the efficiency requirement of the resulting RFE. Then we present two concrete global slotted RBE from pairings and lattices, respectively. With proposed compiler, we hence obtain two bounded collusion-resistant RFE schemes. Here, the first scheme relies on k-Lin assumption, while the second one supports unbounded users under LWE and evasive LWE assumptions.

Clustering is a crucial unsupervised learning method extensively used in the field of data analysis. For analyzing big data, outsourced computation is an effective solution but privacy concerns arise when involving sensitive information. Fully homomorphic encryption (FHE) enables computations on encrypted data, making it ideal for such scenarios. However, existing privacy-preserving clustering based on FHE are often constrained by the high computational overhead incurred from FHE, typically requiring decryption and interactions after only one iteration of the clustering algorithm. In this work, we propose a more efficient approach to evaluate the one-hot vector for the index of the minimum in an array with FHE, which fully exploits the parallelism of single-instruction-multiple-data of FHE schemes. By combining this with FHE bootstrapping, we present a practical FHE-based k-means clustering protocol whose required round of interactions between the data owner and the server is optimal, i.e., accomplishing the entire clustering process on encrypted data in a single round. We implement this protocol using the CKKS FHE scheme. Experiments show that our protocol significantly outperforms the state-of-the-art FHE-based k-means clustering protocols on various public datasets and achieves comparable accuracy to plaintext result. Additionally, We adapt our protocol to support mini-batch k-means for large-scale datasets and report its performance.

In this writeup we discuss the soundness of the Basefold multilinear polynomial commitment scheme [Zeilberger, Chen, Fisch 23] applied to Reed-Solomon codes, and run with proximity parameters up to the Johnson list decoding bound. Our security analysis relies on a generalization of the celebrated correlated agreement theorem from [Ben-Sasson, et al., 20] to linear subcodes of Reed-Solomon codes, which turns out a by-product of the Guruswami-Sudan list decoder analysis. We further highlight a non-linear variant of the subcode correlated agreement theorem, which is flexible enough to apply to Basefold-like protocols such as recent optimizations of FRI-Binius [Diamond, Posen 24], and which we believe sufficient for proving the security of a recent multilinear version of STIR [Arnon, Chiesa, Fenzi, Yogev 24] in the list-decoding regime

We show that there exists a unitary quantum oracle relative to which quantum commitments exist but no (efficiently verifiable) one-way state generators exist. Both have been widely considered candidates for replacing one-way functions as the minimal assumption for cryptography—the weakest cryptographic assumption implied by all of computational cryptography. Recent work has shown that commitments can be constructed from one-way state generators, but the other direction has remained open. Our results rule out any black-box construction, and thus settle this crucial open problem, suggesting that quantum commitments (as well as its equivalency class of EFI pairs, quantum oblivious transfer, and secure quantum multiparty computation) appear to be strictly weakest among all known cryptographic primitives.

We extend the usual ideal action on oriented elliptic curves to a (Hermitian) module action on oriented (polarised) abelian varieties. Oriented abelian varieties are naturally enriched in $R$-modules, and our module action comes from the canonical power object construction on categories enriched in a closed symmetric monoidal category. In particular our action is canonical and gives a fully fledged symmetric monoidal action. Furthermore, we give algorithms to compute this action in practice, generalising the usual algorithms in rank~$1$. The action allows us to unify in the same framework, on the one hand isogeny based cryptography based on ordinary or oriented elliptic curves, and on the other hand the one based on supersingular elliptic curves defined over $\mathbb{F}_{p^2}$. In particular, from our point of view, supersingular elliptic curves over $\mathbb{F}_p$ are given by a rank~$1$ module action, while (the Weil restriction) of those defined over $\mathbb{F}_{p^2}$ are given by a rank~$2$ module action. As a consequence, rank~$2$ module action inversion is at least as hard as the supersingular isogeny path problem. We thus propose to use Hermitian modules as an avatar of a cryptographic symmetric monoidal action framework. This generalizes the more standard cryptographic group action framework, and still allows for a NIKE (Non Interactive Key Exchange). The main advantage of our action is that, presumably, Kuperberg's algorithm does not apply. Compared to CSIDH, this allows for more compact keys and much better scaling properties. In practice, we propose the key exchange scheme $\otimes$-MIKE (Tensor Module Isogeny Key Exchange). Alice and Bob start from a supersingular elliptic curve $E_0/\mathbb{F}_p$ and both compute a $2^n$-isogeny over $\mathbb{F}_{p^2}$. They each send the $j$-invariant of their curve. Crucially, unlike SIDH, no torsion information at all is required. Their common secret, given by the module action, is then a dimension~$4$ principally polarised abelian variety. We obtain a very compact post-quantum NIKE: only 64B for NIST level~$1$ security.

Recently, deep learning-based side-channel analysis (DLSCA) has emerged as a serious threat against cryptographic implementations. These methods can efficiently break implementations protected with various countermeasures while needing limited manual intervention. To effectively protect implementation, it is therefore crucial to be able to interpret \textbf{how} these models are defeating countermeasures. Several works have attempted to gain a better understanding of the mechanics of these models. However, a fine-grained description remains elusive. To help tackle this challenge, we propose using Kolmogorov-Arnold Networks (KANs). These neural networks were recently introduced and showed competitive performance to multilayer perceptrons (MLPs) on small-scale tasks while being easier to interpret. In this work, we show that KANs are well suited to SCA, performing similarly to MLPs across both simulated and real-world traces. Furthermore, we find specific strategies that the trained models learn for combining mask shares and are able to measure what points in the trace are relevant.

Shaped prime moduli are often considered for use in elliptic curve and isogeny-based cryptography to allow for faster modular reduction. Here we focus on the most common choices for shaped primes that have been suggested, that is pseudo-Mersenne, generalized Mersenne and Montgomery-friendly primes. We consider how best to to exploit these shapes for maximum efficiency, and provide an open source tool to automatically generate, test and time working high-level language finite-field code. Next we consider the advantage to be gained from implementations that are written in assembly language and which exploit special instructions, SIMD hardware if present, and the particularities of the algorithm being implemented.

We present the first rigorous dynamic analysis of BKZ, the most widely used lattice reduction algorithm besides LLL: we provide guarantees on the quality of the current lattice basis during execution. Previous analyses were either heuristic or only applied to theoretical variants of BKZ, not the real BKZ implemented in software libraries. Our analysis extends to a generic BKZ algorithm where the SVP-oracle is replaced by an approximate oracle and/or the basis update is not necessarily performed by LLL. As an application, we observe that in certain approximation regimes, it is more efficient to use BKZ with an approximate rather than exact SVP-oracle.

Coppersmith's method plays an important role in cryptanalysis. By introducing a new tool called Sumsets theory from Additive Combinatorics, we propose a novel strategy for Coppersmith's method based on Newton polytope. With our novel strategy, we provide the first provable and efficient algorithm for calculating the asymptotic bounds of Coppersmith's method, which is typically a tedious and non-trivial task. Moreover, our new perspective offers a better understanding of Coppersmith's method. As a byproduct, we apply our new technique and prove the new heuristic introduced by Meers and Nowakowski at Asiacrypt'23 and improve the cryptanalytic result for the Commutative Isogeny Hidden Number Problem.

Fully Homomorphic Encryption (FHE) is a powerful tool for performing privacy-preserving analytics over encrypted data. A promising method for FHE over real and complex numbers is approximate homomorphic encryption, instantiated with the Cheon-Kim-Kim-Song (CKKS) scheme. The CKKS scheme enables efficient evaluation for many privacy-preserving machine learning applications. While the efficiency advantages of CKKS are clear, there is currently a lot of confusion on how to securely instantiate the scheme for any given application, especially after secret-key recovery attacks were discovered by Li and Micciancio (EUROCRYPT'21) for the $IND-CPA^D$ setting, i.e., where decryption results are shared with other parties. On the one hand, the generic definition of $IND-CPA^D$ is application-agnostic and often requires impractically large parameters. On the other hand, practical CKKS implementations target specific applications and use tighter parameters. A good illustration are the recent secret-key recovery attacks against a CKKS implementation in the OpenFHE library by Guo et al. (USENIX Security'24). These attacks misuse the library by employing different circuits during parameter estimation and run-time computation, yet they do not violate the generic (application-agnostic) $IND-CPA^D$ definition. To address this confusion, we introduce the notion of application-aware homomorphic encryption and devise related security definitions, which correspond more closely to how homomorphic encryption schemes are implemented and used in practice. We then formulate the guidelines for implementing the application-aware homomorphic encryption model to achieve $IND-CPA^D$ security for practical applications of CKKS. We also show that our application-aware model can be used for secure, efficient instantiation of exact homomorphic encryption schemes.

While in classical cryptography, one-way functions (OWFs) are widely regarded as the “minimal assumption,” the situation in quantum cryptography is less clear. Recent works have put forward two concurrent candidates for the minimal assumption in quantum cryptography: One-way state generators (OWSGs), postulating the existence of a hard search problem with an efficient verification algorithm, and EFI pairs, postulating the existence of a hard distinguishing problem. Two recent papers [Khurana and Tomer STOC’24; Batra and Jain FOCS’24] showed that OWSGs imply EFI pairs, but the reverse direction remained open. In this work, we give strong evidence that the opposite direction does not hold: We show that there is a quantum unitary oracle relative to which EFI pairs exist, but OWSGs do not. In fact, we show a slightly stronger statement that holds also for EFI pairs that output classical bits (QEFID). As a consequence, we separate, via our oracle, QEFID, and one-way puzzles from OWSGs and several other Microcrypt primitives, including efficiently verifiable one-way puzzles and unclonable state generators. In particular, this solves a problem left open in [Chung, Goldin, and Gray Crypto’24]. Using similar techniques, we also establish a fully black-box separation (which is slightly weaker than an oracle separation) between private-key quantum money schemes and QEFID pairs. One conceptual implication of our work is that the existence of an efficient verification algorithm may lead to qualitatively stronger primitives in quantum cryptography.

In this work, we put forth the notion of dynamic zk-SNARKs. A dynamic zk-SNARK is a zk-SNARK that has an additional update algorithm. The update algorithm takes as input a valid source statement-witness pair $(x,w)\in \mathcal{L}$ along with a verifying proof $\pi$, and a valid target statement-witness pair $(x',w')\in \mathcal{L}$. It outputs a verifying proof $\pi'$ for $(x',w')$ in sublinear time (for $(x,w)$ and $(x',w')$ with small Hamming distance) potentially with the help of a data structure. To the best of our knowledge, none of the commonly-used zk-SNARKs are dynamic---a single update in $(x,w)$ can be handled only by recomputing the proof, which requires at least linear time. After presenting the formal definition of dynamic zk-SNARKs, we provide two constructions. The first one is based on recursive SNARKs and has $O(\log n)$ update time. However it suffers from heuristic security---it must encode the random oracle in the SNARK circuit. The second one and our central contribution, $\mathsf{Dynaverse}$, is based solely on KZG commitments and has $O(\sqrt{n}\log n)$ update time. Our preliminary evaluation shows, that, while worse asymptotically, $\mathsf{Dynaverse}$ outperforms the recursive-based approach by at least one order of magnitude.

The Fiat-Shamir transformation is a key technique for removing interactivity from cryptographic proof systems in real-world applications. In this work, we discuss five types of Fiat-Shamir-related protocol design errors and illustrate them with concrete examples mainly taken from real-life applications. We discuss countermeasures for such vulnerabilities.

Secure key leasing (a.k.a. key-revocable cryptography) enables us to lease a cryptographic key as a quantum state in such a way that the key can be later revoked in a verifiable manner. We propose a simple framework for constructing cryptographic primitives with secure key leasing via the certified deletion property of BB84 states. Based on our framework, we obtain the following schemes. - A public key encryption scheme with secure key leasing that has classical revocation based on any IND-CPA secure public key encryption scheme. Prior works rely on either quantum revocation or stronger assumptions such as the quantum hardness of the learning with errors (LWE) problem. - A pseudorandom function with secure key leasing that has classical revocation based on one-way functions. Prior works rely on stronger assumptions such as the quantum hardness of the LWE problem. - A digital signature scheme with secure key leasing that has classical revocation based on the quantum hardness of the short integer solution (SIS) problem. Our construction has static signing keys, i.e., the state of a signing key almost does not change before and after signing. Prior constructions either rely on non-static signing keys or indistinguishability obfuscation to achieve a stronger goal of copy-protection. In addition, all of our schemes remain secure even if a verification key for revocation is leaked after the adversary submits a valid certificate of deletion. To our knowledge, all prior constructions are totally broken in this setting. Moreover, in our view, our security proofs are much simpler than those for existing schemes.

Side-channel analysis (SCA) compromises the security of cryptographic devices by exploiting various side-channel leakages such as power consumption, electromagnetic (EM) emanations, or timing variations, posing a practical threat to the security and privacy of modern digital systems. In power or EM SCA, statistical or machine learning methods are employed to extract secret information from power/EM traces. In many practical scenarios, raw power/EM traces can span hundreds of thousands of features, with relevant leakages occurring over only a few small segments. Consequently, existing SCAs often select a small number of features before launching the attack, making their success highly dependent on the feasibility of feature selection. However, feature selection may not always be possible, such as in the presence of countermeasures like masking or jitters. Several recent works have employed deep learning (DL) methods to conduct SCA on long raw traces, thereby reducing dependence on feature selection steps. However, these methods often perform poorly against various jitter-based countermeasures. While some of these methods have shown high robustness to several jitter-based countermeasures on relatively shorter traces, we demonstrate in this work that their performance deteriorates as trace lengths increase. To mitigate these limitations of the existing models, we develop a hierarchical DL model for SCA on long traces that is effective against masking, random delay, and clock jitter countermeasures. The proposed model, HierNet, extracts information from long traces using a two-level information assimilation process. At the base level, a DL model with shift-invariance is employed to extract information from smaller trace segments. Subsequently, a top-level DL model integrates the outputs of the base model to generate the final output. HierNet has been experimentally evaluated against various combinations of masking, random delay, and clock jitter countermeasures, using traces up to 250K features long. The results have been compared with three existing SCA benchmark models. They demonstrate HierNet's superiority in several scenarios, such as on long traces or against clock jitter countermeasures, showcasing the ability of HierNet to reach the guessing entropy 1 using fewer than or close to 10 attack traces while the benchmark models fail to do the same using as many as 5K attack traces. Additionally, HierNet exhibits significantly better performance in low-training-data scenarios.

SQIsign is a well-known post-quantum signature scheme due to its small combined signature and public-key size. However, SQIsign suffers from notably long signing times, and verification times are not short either. To improve this, recent research has explored both one-dimensional and two-dimensional variants of SQIsign, each with distinct characteristics. In particular, SQIsign2D’s efficient signing and verification times have made it a focal point of recent research. However, the absence of an optimized one-dimensional verification implementation hampers a thorough comparison between these different variants. This work bridges this gap in the literature: we provide a state-of-the-art implementation of one-dimensional SQIsign verification, including novel optimizations. We report a record-breaking one-dimensional SQIsign verification time of 8.6 Ice Lake Mcycles, closely matching SQIsign2D. For uncompressed signatures, the signature size doubles and we verify in only 5.6 Mcycles. Taking advantage of the inherent parallelism available in isogeny computations, we present 5-core variants that can go as low as 1.3 Mcycles. Furthermore, we present the first implementation that supports both 32-bit and 64-bit processors. It includes optimized assembly code for the Cortex-M4 and has been integrated with the pqm4 project. Our results motivate further research into one-dimensional SQIsign, as it boasts unique features among isogeny-based schemes.

Peer-to-peer energy trading markets enable users to exchange electricity, directly offering them increased financial benefits. However, discrepancies often arise between the electricity volumes committed to in trading auctions and the volumes actually consumed or injected. Solutions designed to address this issue often require access to sensitive information that should be kept private. This paper presents a novel, fully privacy-preserving billing protocol designed to protect users' sensitive consumption and production data in the context of billing protocols for energy trading. Leveraging advanced cryptographic techniques, including fully homomorphic encryption (FHE) and pseudorandom zero sharing (PRZS), our protocol ensures robust security and confidentiality while addressing the critical issue of managing discrepancies between promised and actual electricity volumes. The proposed protocol guarantees that users' sensitive information remains inaccessible to external parties, including the trading platform and billing server. By utilizing FHE, the protocol allows computations on encrypted data without compromising privacy, while PRZS ensures secure aggregation of individual discrepancies of each household. This combination of cryptographic primitives maintains data privacy and enhances billing accuracy, even when fluctuations in energy supply and demand occur. We analyze real-time consumption and production data from 100 households to experimentally validate the effectiveness and efficiency of our billing model. By implementing a flexible framework compatible with any billing method, we demonstrate that our protocol can accurately compute individual bills for 100 households in approximately 0.17 seconds.

Despite much progress, general-purpose secure multi-party computation (MPC) with active security may still be prohibitively expensive in settings with large input datasets. This particularly applies to the secure evaluation of graph algorithms, where each party holds a subset of a large graph. Recently, Araki et al. (ACM CCS '21) showed that dedicated solutions may provide significantly better efficiency if the input graph is sparse. In particular, they provide an efficient protocol for the secure evaluation of "message passing" algorithms, such as the PageRank algorithm. Their protocol's computation and communication complexity are both $\tilde{O}(M\cdot B)$ instead of the $O(M^2)$ complexity achieved by general-purpose MPC protocols, where $M$ denotes the number of nodes and $B$ the (average) number of incoming edges per node. On the downside, their approach achieves only a relatively weak security notion; $1$-out-of-$3$ malicious security with selective abort. In this work, we show that PageRank can instead be captured efficiently as a restricted multiplication straight-line (RMS) program, and present a new actively secure MPC protocol tailored to handle RMS programs. In particular, we show that the local knowledge of the participants can be leveraged towards the first maliciously-secure protocol with communication complexity linear in $M$, independently of the sparsity of the graph. We present two variants of our protocol. In our communication-optimized protocol, going from semi-honest to malicious security only introduces a small communication overhead, but results in quadratic computation complexity $O(M^2)$. In our balanced protocol, we still achieve a linear communication complexity $O(M)$, although with worse constants, but a significantly better computational complexity scaling with $O(M\cdot B)$. Additionally, our protocols achieve security with identifiable abort and can tolerate up to $n-1$ corruptions.

A Private Set Union (PSU) allows two parties having sets $X$ and $Y$ to securely compute the union $X \cup Y$ while revealing no additional information. Recently, there have been proposed so-called shuffle-based PSU protocols due to Garimella et. al. (PKC'21) and Jia et. al. (USENIX'22). Except a few base oblivious transfers, those proposals are fully based on symmetric key primitives and hence enjoy quite low computation costs. However, they commonly have drawbacks on large communication cost of $O(\ell n\log n)$ with input set size $n$ and $\ell \ge O(\lambda + \log n)$ where $\lambda$ is a statistical security parameter. We propose two optimizations for each work that reduce communication cost while maintaining strength in computation cost; the first one optimizes Garimella et. al. to have $O(\ell n + n \log n)$, and the second one optimizes Jia et. al. by reducing the concrete value of $\ell$ by $\log n$. Concretely, the first (second, resp) optimization provides $3.3 - 3.9$x ($1.7 - 1.8$x, resp) lower communication input set sizes $n = 2^{16} - 2^{20}$. We demonstrate by comprehensive analysis and implementation that our optimization leads to better PSU protocol, compared to the state-of-the-art proposal of Zhang et. al. (USENIX'23) as well as previous shuffle-based PSUs. As a concrete amount of improvement, we see $1.4-1.5$x speed up for $100$Mbps network, and $1.8-2.2$x speed up for $10$Mbps network on input set sizes $n = 2^{16} - 2^{20}$.

Threshold public key encryption schemes distribute secret keys among multiple parties, known as the committee, to reduce reliance on a single trusted entity. However, existing schemes face inefficiencies as the committee should perform computation and communication for decryption of each individual ciphertext. As the number of ciphertexts being decrypted per unit of time increases, this can limit the number of committee parties and their decentralization due to increased hardware requirements, heightening the risk of adversarial collusion. To address this, we introduce tag-based batched threshold encryption (TBTE), which ensures constant computational and communication costs per committee member, independent of the number of ciphertexts being decrypted in batch under distinct decryption policies. The TBTE scheme is constructed over bilinear groups in the random oracle model and secure in the algebraic group model, assuming the hardness of the $(q_1,q_2)$-discrete logarithm problem and the EAV-security of the symmetric-key encryption scheme. Evaluation of our implementation demonstrates constant data size, specifically 48 bytes received and 56 bytes sent, and constant execution time for each committee party during decryption, even for various batch sizes up to $2^{20}$.

This paper reveals a critical flaw in the design of ARADI, a recently proposed low-latency block cipher by NSA researchers -- Patricia Greene, Mark Motley, and Bryan Weeks. The weakness exploits the specific composition of Toffoli gates in the round function of ARADI's nonlinear layer, and it allows the extension of a given algebraic distinguisher to one extra round without any change in the data complexity. More precisely, we show that the cube-sum values, though depending on the secret key bits, are always equal in two of the state words. Such a structural property is difficult to obtain by the direct application of division property and has never been seen before in any state-of-the-art block cipher. We call this structural property \textit{weakly-composed-Toffoli gates}, and introduce a theoretical framework which can describe it in general terms. We present algebraic distinguishers that reach 8 out of 16 rounds of ARADI. Most notably, we show that these distinguishers have better data complexities than the division property-based distinguishers for the same number of rounds. We further investigate whether changing the linear layer or the order of composition of Toffoli gates could avoid this property. We give a negative answer to the same and show that it is impossible to prevent this structural property unless the nonlinear layer is re-designed. As a side result, we provide a key-recovery attack on 10 rounds ARADI with $2^{124}$ data and $2^{177}$ time for a 256-bit key. Our work highlights the significance of security analysis during the cipher design phase, and shows that these strong structural distinguishers could have been avoided during this phase.

Succinct arguments of knowledge allow an untrusted prover to establish that they know a witness for an NP relation. Many recent efficient constructions of such schemes work over arithmetic computations expressed in finite fields. Several common settings, however, have an extremely simple representation when expressed over the integers (e.g., RSA signatures/accumulators, range checks for committed values, computations over rational numbers). Efficient arguments of knowledge working natively over $\mathbb{Z}$ could be applied to such computations without the overhead from emulating integer arithmetic over a finite field. We propose the first native construction of SNARKs over the integers that is fully succinct, thus resolving an open problem from Towa and Vergnaud (Asiacrypt 2020). By fully succinct, we mean that \textit{both} the proof size and the verifier's running time should be sublinear in both $|\vec w|$—the size of the witness as a vector of integers—and $\log_2 \lVert \vec w \rVert_\infty$—the size in bits of the largest integer in the witness vector (in absolute value). As a stepping stone for our results we provide a general theoretical framework for building succinct arguments over the integers. Its most attractive feature is that it allows to reuse already existing constructions of SNARKs in a modular way and can be used as a starting point for constructions following up our work. We build these systematic foundations by leveraging a common technique in theoretical computer science—fingerprinting—and applying it to a new setting. Our framework consists of two main ingredients: idealized protocols and polynomial commitments such that an object ``committed over the integers'' can however be ``queried modulo $q$'', for a randomly sampled prime $q$. We obtain our final construction, $\mathbb{Z}$aratan, by lifting the $\mathsf{Spartan}$ construction (Setty, CRYPTO 2020) to the integers and applying a form of polynomial commitment based on the techniques from DARK (Bünz et al., Eurocrypt 2020). $\mathbb{Z}$aratan has a transparent setup, is proven secure in the generic group model for groups of unknown order and can be heuristically made non-interactive in the ROM via the Fiat-Shamir transform.

Deep neural networks have proven effective for second-order profiling side-channel attacks, even in a black-box setting with no prior knowledge of masks and implementation details. While such attacks have been successful, no explanations were provided for understanding why a variety of deep neural networks can (or cannot) learn high-order leakages and what the limitations are. In other words, we lack the explainability on neural network layers combining (or not) unknown and random secret shares, which is a necessary step to defeat, e.g., Boolean masking countermeasures. In this paper, we use information-theoretic metrics to explain the internal activities of deep neural network layers. We propose a novel methodology for the explainability of deep learning-based profiling side-channel analysis (denoted ExDL-SCA) to understand the processing of secret masks. Inspired by the Information Bottleneck theory, our explainability methodology uses perceived information to explain and detect the different phenomena that occur in deep neural networks, such as fitting, compression, and generalization. We provide experimental results on masked AES datasets showing what relevant features deep neural networks use, and where in the networks relevant features are learned and irrelevant features are compressed. Using our method, evaluators can determine what secret masks are being exploited by the network, which allows for more detailed feedback on the implementations. This paper opens new perspectives for understanding the role of different neural network layers in profiling side-channel attacks.

Isogeny-based cryptography is cryptographic schemes whose security is based on the hardness of a mathematical problem called the isogeny problem, and is attracting attention as one of the candidates for post-quantum cryptography. A representative isogeny-based cryptography is the signature scheme called SQIsign, which was submitted to the NIST PQC standardization competition. SQIsign has attracted much attention because of its very short signature and key size among the candidates for the NIST PQC standardization. Recently, a lot of new schemes have been proposed that use high-dimensional isogenies. Among them, the signature scheme called SQIsignHD has an even shorter signature size than SQIsign. However, it requires 4-dimensional isogeny computations for the signature verification. In this paper, we propose a new signature scheme, SQIsign2D-East, which requires only two-dimensional isogeny computations for verification, thus reducing the computational cost of verification. First, we generalized an algorithm called RandIsogImg, which computes a random isogeny of non-smooth degree. Then, by using this generalized RandIsogImg, we construct a new signature scheme SQIsign2D-East.

Lookup arguments have recently attracted a lot of developments due to their applications in the constructions of succinct non-interactive arguments of knowledge (SNARKs). A closely related topic is subsequence arguments in which one can prove that string $\mathbf{s}$ is a subsequence of another string $\mathbf{t}$, i.e., deleting some characters in $\mathbf{t}$ can achieve $\mathbf{s}$. A dual notion, namely, non-subsequence arguments, is to prove that $\mathbf{s}$ is not a subsequence of $\mathbf{t}$. These problems have a lot of important applications in DNA sequence analysis, internet of things, blockchains, natural language processing, speech recognition, etc. However, despite their applications, they are not well-studied in cryptography, especially succinct arguments for non-subsequences with efficient proving time and sublinear verification time. In this work, we propose the first succinct non-subsequence argument. Our solution applies the sumcheck protocol and is instantiable by any multivariate polynomial commitment schemes (PCSs). We achieve an efficient prover whose running time is linear in the size of sequences $\mathbf{s}$, $\mathbf{t}$ and their respective alphabet $\Sigma$. Our proof is succinct and the verifier time is sublinear assuming the employed PCS has succinct commitments and sublinear verification time. When instantiating with Sona PCS (EUROCRYPT'24), we achieve proof size $\mathcal{O}(\log_2|\mathbf{s}| + \log_2|\mathbf{t}|+\log_2|\Sigma|)$, prover time $\mathcal{O}(|\mathbf{s}|+|\mathbf{t}|+|\Sigma|)$ and verifier time $\mathcal{O}(\sqrt{|\mathbf{s}|}+\sqrt{|\mathbf{t}|}+\sqrt{|\Sigma|})$. Extending our technique, we can achieve a batch subsequence argument for proving in batch $k$ interleaving subsequence and non-subsequence arguments without proof size suffering a linear blow-up in $k$.

Nova is a new type of recursive proof system that uses a folding scheme as its core building block. This brilliant idea of folding relations can significantly reduce the recursion overhead. In this paper, we study some issues related to Nova’s soundness proof, which relies on the soundness of the folding scheme in a recursive manner. First, due to its recursive nature, the proof strategy inevitably causes the running time of the recursive extractor to expand polynomially for each additional recursive step. This constrains Nova's soundness model to only logarithmically bounded recursive steps. Consequently, the soundness proof in this limited model does not guarantee soundness for a linear number of rounds in the security parameter, such as 128 rounds for 128-bit security. On the other hand, there are no known attacks on the arbitrary depth recursion of Nova, leaving a gap between theoretical security guarantees and real-world attacks. We aim to bridge this gap in two opposite directions. In the negative direction, we present a recursive proof system that is unforgeable in a log-round model but forgeable if used in linear rounds. This shows that the soundness proof in the log-round model might not be applicable to real-world applications that require linearly long rounds. In a positive direction, we show that when Nova uses a specific group-based folding scheme, its knowledge soundness over polynomial rounds can be proven in the algebraic group model with our modifications. To the best of our knowledge, this is the first result to show Nova's polynomial rounds soundness. Second, the folding scheme is converted non-interactively via the Fiat-Shamir transformation and then arithmetized into R1CS. Therefore, the soundness of Nova using the non-interactive folding scheme essentially relies on the heuristic random oracle instantiation in the standard model. In our new soundness proof for Nova in the algebraic group model, we replace this heuristic with a cryptographic hash function with a special property. We view this hash function as an independent object of interest and expect it to help further understand the soundness of Nova.

Searchable encryption, or more generally, structured encryption, permits search over encrypted data. It is an important cryptographic tool for securing cloud storage. The standard security notion for structured encryption mandates that a protocol leaks nothing about the data or queries, except for some allowed leakage, defined by the leakage function. This is due to the fact that some leakage is unavoidable for efficient schemes. Unfortunately, it was shown by numerous works that even innocuous-looking leakage can often be exploited by attackers to undermine users' privacy and recover their queries and/or data, despite the structured encryption schemes being provably secure. Nevertheless, the standard security remains the go-to notion used to show the "security" of structured encryption schemes. While it is not likely that researchers will design practical structured encryption schemes with no leakage, it is not satisfactory that very few works study ways to assess leakage. This work proposes a novel framework to quantify leakage. Our methodology is inspired by the quantitative information flow, and we call our method $q$-leakage analysis. We show how $q$-leakage analysis is related to the standard security. We also demonstrate the usefulness of $q$-leakage analysis by analyzing the security of two existing schemes with complex leakage functions.

In this work we demonstrate for the first time that a full FHE bootstrapping operation can be proven using a SNARK in practice. We do so by designing an arithmetic circuit for the bootstrapping operation and prove it using plonky2. We are able to prove the circuit on an AWS Hpc7a instance in under 20 minutes. Proof size is about 200kB and verification takes less than 10ms. As the basis of our bootstrapping operation we use TFHE's programmable bootstrapping and modify it in a few places to more efficiently represent it as an arithmetic circuit (while maintaining full functionality and security). In order to achieve our results in a memory-efficient way, we take advantage of the structure of the computation and plonky2's ability to efficiently prove its own verification circuit to implement a recursion-based IVC scheme. Lastly, we present a security proof in the UC model that captures active attacks in real world applications of verifiable FHE and augment our prototype to fit such applications.

A monotone policy batch $\mathsf{NP}$ language $\mathcal{L}_{\mathcal{R}, P}$ is parameterized by a monotone policy $P \colon \{0,1\}^k \to \{0,1\}$ and an $\mathsf{NP}$ relation $\mathcal{R}$. A statement $(x_1, \ldots, x_k)$ is a YES instance if there exists $w_1, \ldots, w_k$ where $P(\mathcal{R}(x_1, w_1), \ldots, \mathcal{R}(x_k, w_k)) = 1$. For example, we might say that an instance $(x_1, \ldots, x_k)$ is a YES instance if a majority of the statements are true. A monotone policy batch argument (BARG) for $\mathsf{NP}$ allows a prover to prove that $(x_1, \ldots, x_k) \in \mathcal{L}_{\mathcal{R}, P}$ with a proof of size $\mathsf{poly}(\lambda, |\mathcal{R}|, \log k)$, where $\lambda$ is the security parameter, $|\mathcal{R}|$ is the size of the Boolean circuit that computes $\mathcal{R}$, and $k$ is the number of instances. Recently, Brakerski, Brodsky, Kalai, Lombardi, and Paneth (CRYPTO 2023) gave the first monotone policy BARG for $\mathsf{NP}$ from the learning with errors (LWE) assumption. In this work, we describe a generic approach for constructing monotone policy BARGs from any BARG for $\mathsf{NP}$ together with an additively homomorphic encryption scheme. This yields the first constructions of monotone policy BARGs from the $k$-$\mathsf{Lin}$ assumption in prime-order pairing groups as well as the (subexponential) DDH assumption in pairing-free groups. Central to our construction is a notion of a zero-fixing hash function, which is a relaxed version of a predicate-extractable hash function from the work of Brakerski et al. Our relaxation enables a direct realization of zero-fixing hash functions from BARGs for $\mathsf{NP}$ and additively homomorphic encryption, whereas the previous notion relied on leveled homomorphic encryption, and by extension, the LWE assumption. As an application, we also show how to combine a monotone policy BARG with a puncturable signature scheme to obtain a monotone policy aggregate signature scheme. Our work yields the first (statically-secure) monotone policy aggregate signatures that supports general monotone Boolean circuits from standard pairing-based assumptions. Previously, this was only known from LWE.

Threshold signatures have been drawing lots of attention in recent years. Of particular interest are threshold signatures that are proven secure under adaptive corruptions (NIST Call 2023). Sadly, existing constructions with provable adaptive security suffer from at least one of the following drawbacks: (i) strong idealizations such as the algebraic group model (AGM), (ii) an unnatural restriction on the corruption threshold being $t/2$ where $t$ is the signing threshold, or (iii) prohibitively large security loss under established assumptions. Notably, point (iii) has received little to no attention in the literature on this subject. In this work, we introduce Twinkle-T, a new threshold signature scheme which overcomes these limitations. Twinkle-T is the first scheme to have a fully tight security proof under up to $t$ adaptive corruptions without relying on the AGM. It also has a signing protocol consisting of only three rounds and thus matches the currently best threshold signature with full adaptive security Twinkle (Eurocrypt 2024) in the pairing-free discrete logarithm setting. We prove security from a standard non-interactive assumption, namely, the Decisional Diffie-Hellman (DDH) assumption.

Laconic cryptography studies two-message protocols that securely compute on large amounts of data with minimal communication cost. Laconic oblivious transfer (OT) is a central primitive where the receiver's input is a large database $\mathsf{DB}$ and the sender's inputs are two messages $m_0$, $m_1$ along with an index $i$, such that the receiver learns the message determined by the choice bit $\mathsf{DB}_i$. OT becomes even more useful for secure computation when considering its laconic variants, which offer succinctness and round optimality. However, existing constructions are not practically efficient because they rely on heavy cryptographic machinery and non-black-box techniques. In this work, we initiate the study of laconic OT correlations, where the model allows an offline phase to generate the correlations later used in a lightweight online phase. Our correlation is conceptually simple, captured by an inner product computation, and enables us to achieve a private laconic OT protocol where the sender's index $i$ is also hidden from the receiver. Our construction is the first private laconic OT with database-dependent preprocessing based solely on symmetric-key assumptions, achieving sublinear online computational complexity for the receiver. Furthermore, we enhance our construction with updatability and receiver privacy. Finally, we demonstrate the applications of private laconic OT to laconic function evaluation for RAM programs and laconic private set intersection with preprocessing.

This work describes a digital signature scheme constructed from a zero-knowledge proof of knowledge of a pre-image of the Rescue Prime Optimized (RPO) permutation. The proof of knowledge is constructed with the DEEP-ALI interactive oracle proof combined with the Ben-Sasson--Chiesa--Spooner (BCS) transformation in the random oracle model. The EUF-CMA security of the resulting signature scheme is established from the UC-friendly security properties of the BCS transformation and the pre-image hardness of the RPO permutation. The implementation of the scheme computes signatures in 13 ms and verifies them in 1 ms on a single core when the BCS transform is implemented with the Blake3 hash function. (The multi-threaded implementation signs in 9.2 ms and also verifies in 1 ms.) These speeds are obtained with parameters achieving 122 bits of average-case security for \( 2^{122} \)-bounded adversaries with access to at most \( 2^{64} \) signatures.

Keyed-verification anonymous credentials are widely recognized as among the most efficient tools for anonymous authentication. In this work, we revisit two prominent credential systems: the scheme by Chase et al. (CCS 2014), commonly referred to as CMZ or PS MAC, and the scheme by Barki et al. (SAC 2016), known as BBDT or BBS MAC. We show how to make CMZ statistically anonymous and BBDT compatible with the BBS RFC draft. We provide a comprehensive security analysis for strong(er) properties of unforgeability and anonymity. These properties allow them to be composed with extensions that users can pick and choose. We show that simpler variants satisfying one-more unforgeability can still be anonymous tokens (Kreuter et al., CRYPTO 2020). To enable faster proofs for complex presentations, we present a compiler that uses an interactive oracle proof and a designated-verifier polynomial commitment to construct a designated-verifier non-interactive argument. For keyed-verification anonymous credentials, designated-verifier proofs suffice since the verifier is known in advance. We explore extensions that could benefit from this approach.

A verifiable delay function (VDF) is a cryptographic primitive that requires a long time to compute (even with parallelization), but produces a unique output that is efficiently and publicly verifiable. We prove that VDFs with \emph{imperfect completeness} and \emph{computational uniqueness} do not exist in the random oracle model. This also rules out black-box constructions of VDFs from other cryptographic primitives, such as one-way permutations and collision-resistant hash functions. Prior to our work, Mahmoody, Smith and Wu (ICALP 2020) prove that VDFs satisfying both \emph{perfect completeness} and \emph{perfect uniqueness} do not exist in the random oracle model; on the other hand, Ephraim, Freitag, Komargodski, and Pass (Eurocrypt 2020) construct VDFs with \emph{perfect completeness} and \emph{computational uniqueness} in the random oracle model assuming the hardness of repeated squaring. Our result is optimal -- we bridge the current gap between previously known impossibility results and existing constructions.

Cryptographic proof systems have a plethora of applications: from building other cryptographic tools (e.g., malicious security for MPC protocols) to concrete settings such as private transactions or rollups. In several settings it is important for proof systems to be non-malleable: an adversary should not to be able to modify a proof they have observed into another for a statement for which they do not know the witness. Proof systems that have been deployed in practice should arguably satisfy this notion: it is crucial in settings such as transaction systems and in order to securely compose proofs with other cryptographic protocols. As a consequence, results on non-malleability should keep up with designs of proofs being deployed. Recently, Arun et al. proposed $\mathsf{Jolt}$ (Eurocrypt 2024), arguably the first efficient proof system whose architecture is based on the lookup singularity approach (Barry Whitehat, 2022). This approach consists in representing a general computation as a series of table lookups. The final result is a SNARK for a Virtual Machine execution (or SNARK VM). Both SNARK VMs and lookup-singularity SNARKs are architectures with enormous potential and will probably be adopted more and more in the next years (and they already are). As of today, however, there is no literature regarding the non-malleability of SNARK VMs. The goal of this work is to fill this gap by providing both concrete non-malleability results and a set of technical tools for a more general study of SNARK VMs security (as well as "modular" SNARKs in general). As a concrete result, we study the non-malleability of (an idealized version of) $\mathsf{Jolt}$ and its fundamental building block, the lookup argument $\mathsf{Lasso}$. While connecting our new result on the non-malleability of $\mathsf{Lasso}$ to that of $\mathsf{Jolt}$, we develop a set of tools that enable the composition of non-malleable SNARKs. We believe this toolbox to be valuable in its own right.

As the industry prepares for the transition to post-quantum secure public key cryptographic algorithms, vulnerability analysis of their implementations is gaining importance. A theoretically secure cryptographic algorithm should also be able to withstand the challenges of physical attacks in real-world environments. MAYO is a candidate in the ongoing first round of the NIST post-quantum standardization process for selecting additional digital signature schemes. This paper demonstrates three first-order single-execution fault injection attacks on a MAYO implementation in an ARM Cortex-M4 processor. By using voltage glitching to disrupt the computation of the vinegar seed during the signature generation, we enable the recovery of the secret key directly from the faulty signatures. Our experimental results show that the success rates of the fault attacks in a single execution are 36%, 82%, and 99%, respectively. They emphasize the importance of developing countermeasures against fault attacks prior to the widespread deployment of post-quantum algorithms like MAYO.

Orion (Xie et al. CRYPTO'22) is a recent plausibly post-quantum zero-knowledge argument system with a linear time prover. It improves over Brakedown (Golovnev et al. ePrint'21 and CRYPTO'23) by reducing the proof size and verifier complexity to be polylogarithmic and additionally adds the zero-knowledge property. The argument system is demonstrated to be concretely efficient with a prover time being the fastest among all existing succinct proof systems and a proof size that is an order of magnitude smaller than Brakedown. Since its publication in CRYPTO 2022, two revisions have been made to the zk-SNARK. First, there was an issue with how zero-knowledge was handled. Second, Orion was discovered to be unsound, which was then repaired through the use of a commit-and-prove SNARK as an "outer" SNARK. As we will show in this paper, unfortunately, Orion in its current revision is still unsound (with and without the zero-knowledge property) and we will demonstrate practical attacks on it. We then show how to repair Orion without additional assumptions, with the resuling polynomial commitment denoted as Scorpius, which requires non-trivial fixes when aiming to preserve the linear time prover complexity. The proposed fixes lead to an even improved efficiency, i.e., smaller proof size and verifier time, over the claimed efficiency of the initial version of Orion. We also apply the recent ideas of Diamond and Posen (CiC'24) to make the challenge in Orion logarithmically sized. Moreover, we provide the first rigorous security proofs and explicitly consider multi-point openings and non-interactivity. While revisiting Orion we make some additional contributions which might be of independent interest, most notable an improved code randomization technique that retains the minimum relative distance.

In this work, we introduce FANNG-MPC, a versatile secure multi-party computation framework capable to offer active security for privacy preserving machine learning as a service (MLaaS). Derived from the now deprecated SCALE-MAMBA, FANNG is a data-oriented fork, featuring novel set of libraries and instructions for realizing private neural networks, effectively reviving the popular framework. To the best of our knowledge, FANNG is the first MPC framework to offer actively secure MLaaS in the dishonest majority setting. FANNG goes beyond SCALE-MAMBA by decoupling offline and online phases and materializing the dealer model in software, enabling a separate set of entities to produce offline material. The framework incorporates database support, a new instruction set for pre-processed material, including garbled circuits and convolutional and matrix multiplication triples. FANNG also implements novel private comparison protocols and an optimized library supporting Neural Network functionality. All our theoretical claims are substantiated by an extensive evaluation using an open-sourced implementation, including the private inference of popular neural networks like LeNet and VGG16.

We use the HHL algorithm to retrieve a quantum state holding the algebraic normal formal of a Boolean function. Unlike the standard HHL applications, we do not describe the cipher as an exponentially big system of equations. Rather, we perform a set of small matrix inversions which corresponds to the Boolean Möbius transform. This creates a superposition holding information about the ANF in the form: $\ket{\mathcal{A}_{f}} =\frac{1}{C} \sum_{I=0}^{2^n-1} c_I \ket{I}$, where $c_I$ is the coefficient of the ANF and $C$ is a scaling factor. The procedure has a time complexity of $\mathcal{O}(n)$ for a Boolean function with $n$ bit input. We also propose two approaches how some information about the ANF can be extracted from such a state.

In this paper, we introduce $\mathsf{DeuringVUF}$, a new Verifiable Unpredictable Function (VUF) protocol based on isogenies between supersingular curves. The most interesting application of this VUF is $\mathsf{DeuringVRF}$ a post-quantum Verifiable Random Function (VRF). The main advantage of this new scheme is its compactness, with combined public key and proof size of roughly 450 bytes, which is orders of magnitude smaller than other generic purpose post-quantum VRF constructions. This scheme is also the first post-quantum VRF satisfying unconditional uniqueness. We show that this scheme is practical by providing a first non-optimized C implementation that runs in roughly 20ms for verification and 350ms for evaluation. The function at the heart of our construction is the one that computes the codomain of an isogeny of big prime degree from its kernel. The evaluation can be performed efficiently with the knowledge of the endomorphism ring using a new ideal-to-isogeny algorithm introduced recently by Basso, Dartois, De Feo, Leroux, Maino, Pope, Robert and Wesolowski that uses computation of dimension $2$ isogenies between elliptic products to compute effectively the translation through the Deuring correspondence of any ideal. On the other hand, without the knowledge of the endomorphism ring, this computation appears to be hard. The security of our $\mathsf{DeuringVUF}$ holds under a new assumption call the one-more isogeny problem (OMIP). Another application of $\mathsf{DeuringVUF}$ is the first hash-and-sign signature based on isogenies in the standard model. While we don't expect the signature in itself to outperform the recent variants of SQIsign, it remains very competitive in both compactness and efficiency while providing a new framework to build isogeny-based signature that could lead to new interesting applications. We also introduce several new algorithms for the effective Deuring correspondence. In particular, we introduce an algorithm to translate an ideal of norm a big power of a small prime $\ell$ into the corresponding isogeny of dimension $1$ using isogenies between abelian variety of dimension $2$ as a tool. This algorithm can be used to improve the SQIsign signature scheme.

Masking is a sound countermeasure to protect against differential power analysis. Since the work by Balasch et al. in ASIACRYPT 2012, inner product masking has been explored as an alternative to the well known Boolean masking. In CARDIS 2017, Poussier et al. showed that inner product masking achieves higher-order security versus Boolean masking, for the same shared size, in the bit-probing model. Wang et al. in TCHES 2020 verified the inner product masking's security order amplification in practice and proposed new gadgets for inner product masking. Finally, Wu et al. in TCHES 2022 showed that this security amplification comes from the bit-probing model, but that Wang al.'s gadgets are not higher-order bit-probing secure reducing the computation's practical security. The authors concluded their work with the open question of providing an inner product multiplication gadget which maintains the masking's bit-probing security, and conjectured that such gadget maintains the practical security order amplification of the masking during its computation. In this paper, we answer positively to Wu et al.'s open problems. We are the first to present a multiplication gadget for inner product masking which is proven secure in the bit-level probing model using the t-Strong Non-Interference (SNI) property. Moreover, we provide practical evidence that the gadget indeed maintains the security amplification of its masking. This is done via an evaluation of an assembly implementation of the gadget on an ARM Cortex-M4 core. We used this implementation to take leakage measurements and show no leakage happens for orders below the gadget's bit-probing security level either for its univariate or multivariate analysis.

Power-of-two cyclotomics is a popular choice when instantiating the BGV scheme because of its efficiency and compliance with the FHE standard. However, in power-of-two cyclotomics, the linear transformations in BGV bootstrapping cannot be decomposed into sub-transformations for acceleration with existing techniques. Thus, they can be highly time-consuming when the number of slots is large, degrading the advantage brought by the SIMD property of the plaintext space. By exploiting the algebraic structure of power-of-two cyclotomics, this paper derives explicit decomposition of the linear transformations in BGV bootstrapping into NTT-like sub-transformations, which are highly efficient to compute homomorphically. Moreover, multiple optimizations are made to evaluate homomorphic linear transformations, including modified BSGS algorithms, trade-offs between level and time, and specific simplifications for thin and general bootstrapping. We implement our method on HElib. With the number of slots ranging from 4096 to 32768, we obtain a 2.4x$\sim$55.1x improvement in bootstrapping throughput, compared to previous works or the naive approach.

For more than two decades, pairings have been a fundamental tool for designing elegant cryptosystems, varying from digital signature schemes to more complex privacy-preserving constructions. However, the advancement of quantum computing threatens to undermine public-key cryptography. Concretely, it is widely accepted that a future large-scale quantum computer would be capable to break any public-key cryptosystem used today, rendering today's public-key cryptography obsolete and mandating the transition to quantum-safe cryptographic solutions. This necessity is enforced by numerous recognized government bodies around the world, including NIST which initiated the first open competition in standardizing post-quantum (PQ) cryptographic schemes, focusing primarily on digital signatures and key encapsulation/public-key encryption schemes. Despite the current efforts in standardizing PQ primitives, the landscape of complex, privacy-preserving cryptographic protocols, e.g., zkSNARKs/zkSTARKs, is at an early stage. Existing solutions suffer from various disadvantages in terms of efficiency and compactness and in addition, they need to undergo the required scrutiny to gain the necessary trust in the academic and industrial domains. Therefore, it is believed that the migration to purely quantum-safe cryptography would require an intermediate step where current classically secure protocols and quantum-safe solutions will co-exist. This is enforced by the report of the Commercial National Security Algorithm Suite version 2.0, mandating transition to quantum-safe cryptographic algorithms by 2033 and suggesting to incorporate ECC at 192-bit security in the meantime. To this end, the present paper aims at providing a comprehensive study on pairings at 192-bit security level. We start with an exhaustive review in the literature to search for all possible recommendations of such pairing constructions, from which we extract the most promising candidates in terms of efficiency and security, with respect to the advanced Special TNFS attacks. Our analysis is focused, not only on the pairing computation itself, but on additional operations that are relevant in pairing-based applications, such as hashing to pairing groups, cofactor clearing and subgroup membership testing. We implement all functionalities of the most promising candidates within the RELIC cryptographic toolkit in order to identify the most efficient pairing implementation at 192-bit security and provide extensive experimental results.

The TLS (Transport Layer Security) protocol is the most important, most attacked, most analysed and most used cryptographic protocol in the world today. TLS is critical to the integrity of the Internet, and if it were to be broken e-commerce would become impossible, with very serious implications for the global economy. Furthermore TLS is likely to assume even greater significance in the near future with the rapid growth of an Internet of Things (IoT) -- a multiplicity of internet connected devices all engaged in secure inter-communication. However the impending invention of a Cryptographically Relevant Quantum Computer (CRQC) would represent an existential threat to TLS in its current form. As it stands the latest version TLS1.3, benefiting as it does from years of research and study, provides effective security, but it must soon be updated to resist this new threat. In this research we first undertake a new clean-room implementation of a small-footprint open source TLS1.3, written in C++ and Rust, and suitable for IoT applications. Our implementation is designed to be cryptographically agile, so that it can easily accomodate new post-quantum cryptographic primitives. Next we use this new implementation as a vehicle to study the impact of going post-quantum, with a particular emphasis on the impact on the Internet of Things. Finally we showcase the flexibility of our implementation by proposing an implementation of TLS that uses identity-based encryption to mitigate this impact.

Modern SNARK designs typically follow a frontend-backend paradigm: The frontend compiles a user's program into some equivalent circuit representation, while the backend calls for a SNARK specifically made for proving circuit satisfiability. While these circuits are often defined over small fields, the backend prover always needs to lift the computation to much larger fields to ensure soundness. This gap introduces concrete overheads for ZK applications like zkRollups, where group-based SNARKs are used to provide constant-size proofs for Merkle tree openings. For a class of highly repetitive computations, we propose $\mathsf{FREPack}$, an improved frontend that effectively bridges this gap. The larger the gap between circuit's small field and backend's large field, the more $\mathsf{FREPack}$ reduces the circuit size, making it particularly well-suited for group-based backends. Our implementation shows that, for proving $\approx 300$ iterations of SHA-256, $\mathsf{FREPack}$ improves the performance of Groth16 by $3.6\times$, Nova by $3.8\times$, and Spartan by $5.9\times$.

Two-party computation has been an active area of research since Yao's breakthrough results on garbled circuits. We present secret key additive somewhat homomorphic schemes where the client has perfect privacy (server can be computationally unbounded). Our basic scheme is additive somewhat homomorphic and we give protocols to handle addition and multiplication. In one scheme, the server handles circuit multiplication gates by returning the multiplicands to the client which does the multiplication and sends back the encrypted product. We give a 2-party protocol that also incorporates server inputs where the client has perfect privacy. Server privacy is not information-theoretic, but rather depends on hardness of the subset sum problem. Correctness for the server in the malicious model can be verified by a 3rd party with high probability where the client and server privacy are information-theoretically protected from the verifier. Scaling the 2PC protocol via separate encryption parameters for smaller subcircuits allows the ciphertext size to remain constant as circuit size grows.

The traditional definition of fully homomorphic encryption (FHE) is not composable, i.e., it does not guarantee that evaluating two (or more) homomorphic computations in a sequence produces correct results. We formally define and investigate a stronger notion of homomorphic encryption which we call "fully composable homomorphic encryption", or "composable FHE". The definition is both simple and powerful: it does not directly involve the evaluation of multiple functions, and yet it supports the arbitrary composition of homomorphic evaluations. On the technical side, we compare the new definition with other definitions proposed in the past, proving both implications and separations, and show how the "bootstrapping" technique of (Gentry, STOC 2009) can be formalized as a method to transform a (non-composable, circular secure) homomorphic encryption scheme into a fully composable one. We use this formalization of bootstrapping to formulate a number of conjectures and open problems.

Decentralized storage networks, including IPFS and Filecoin, have created a marketplace where individuals exchange storage space for profit. These networks employ protocols that reliably ensure data storage providers accurately store data without alterations, safeguarding the interests of storage purchasers. However, these protocols lack an effective and equitable payment mechanism for data retrieval, particularly when multiple data queriers are involved. This necessitates a protocol that ensures both data integrity and fair compensation for data providers. In decentralized storage, data is fragmented into small blocks and stored across multiple nodes, a process known as data swarming. Due to this property, traditional data exchange protocols are inadequate in terms of communication and economic efficiency. We propose the Proof of Unified Data Retrieval protocol (PoUDR). PoUDR incorporates ZK-SNARK to facilitate a fair data exchange protocol. PoUDR reduces the number of blockchain transactions for both single block and data swarming retrieval. The protocol requires only a single key-revealing transaction submitted by the provider to the blockchain for each data block. This architecture allows for further optimization of transaction numbers through a batched proof technique on the provider's side. This approach necessitates only $N_P$ transactions within a specific time frame when data consisting of $N_D$ blocks, provided by $N_P$ providers, is queried by $N_Q$ queriers. This work provides a comprehensive definition for Secure Swarming Data Exchange (SSDE), including security assumptions. Also it offers a detailed game-based security analysis for the PoUDR protocol. Moreover, the PoUDR protocol has been fully integrated into the Bitswap protocol (IPFS). Within this integration, our proposed Relaxed Groth16 algorithm addresses the significant technical challenge of generating zero-knowledge proofs, leading to substantial cost reductions for overall feasibility of secure data retrieval in decentralized storage networks.

HEonGPU is a high-performance library designed to optimize Fully Homomorphic Encryption (FHE) operations on Graphics Processing Unit (GPU). By leveraging the parallel processing capac- ity of GPUs, HEonGPU significantly reduces the computational overhead typically associated with FHE by executing complex operation concurrently. This allows for faster execution of homomorphic computations on encrypted data, enabling real-time applications in privacy-preserving machine learn- ing and secure data processing. A key advantage of HEonGPU lies in its multi-stream architecture, which not only allows parallel processing of tasks to improve throughput but also eliminates the over- head of data transfers between the host device (i.e., CPU) and GPU. By efficiently managing data within the GPU using multi-streams, HEonGPU minimizes the need for repeated memory transfers, further enhancing performance. HEonGPU’s GPU-optimized design makes it ideal for large-scale encrypted computations, providing users with reduced latency and higher performance across various FHE schemes.

RAM (random access memory) is an important primitive in verifiable computation. In this paper, we focus on realizing RAM with efficient batching property, i.e, proving a batch of $m$ updates on a RAM of size $N$ while incurring a cost that is sublinear in $N$. Classical approaches based on Merkle-trees or address ordered transcripts to model RAM correctness are either concretely inefficient, or incur linear overhead in the size of the RAM. Recent works explore cryptographic accumulators based on unknown-order groups (RSA, class-groups) to model the RAM state. While recent RSA accumulator based approaches offer significant improvement over classical methods, they incur linear overhead in the size of the accumulated set to compute witnesses, as well as prohibitive constant overheads. We realize a batching-efficient RAM with superior asymptotic and concrete costs as compared to existing approaches. Towards this: (i) we build on recent constructions of lookup arguments to allow efficient lookups even in presence of table updates, and (ii) we realize a variant of sub-vector relation addressed in prior works, which we call committed index lookup. We combine the two building blocks to realize batching-efficient RAM with sublinear dependence on size of the RAM. Our construction incurs an amortized proving cost of $\tilde{O}(m\log m + \sqrt{mN})$ for a batch of $m$ updates on a RAM of size $N$. Our results also benefit the recent arguments for sub-vector relation, by enabling them to be efficient in presence of updates to the table. We believe that this is a contribution of independent interest. We implement our solution to evaluate its concrete efficiency. Our experiments show that it offers significant improvement over existing works on batching-efficient accumulators/RAMs, with a substantially reduced resource barrier.

There has been a recent interest to develop and standardize Robust Authenticated Encryption (Robust AE) schemes. NIST, for example, is considering an Accordion mode (a wideblock tweakable blockcipher), with Robust AE as a primary application. On the other hand, recent attacks and applications suggest that encryption needs to be committing. Indeed, committing security isalso a design consideration in the Accordion mode. Yet it is unclear how to build a Robust AE with committing security. In this work, we give a modular solution for this problem. We first show how to transform any wideblock tweakable blockcipher TE to a Robust AE scheme SE that commits just the key. The overhead is cheap, just a few finite-field multiplications and blockcipher calls. If one wants to commit the entire encryption context, one can simply hash the context to derive a 256-bit subkey, and uses SE on that subkey. The use of 256-bit key on SE only means that it has to rely on AES-256 but doesn't require TE to have 256-bit key. Our approach frees the Accordion designs from consideration of committing security. Moreover, it gives a big saving for several key-committing applications that don't want to pay the inherent hashing cost of full committing.

State-of-the-art database implementations offer a wide range of functionalities and impressive performances while supporting highly concurrent loads. However they all rely on the server knowing the content of the database, which raises issues when sensitive information is being stored on a server that cannot be trusted. Encrypting documents before sending them to a remote server solves the confidentiality issue at the cost of loosing the keyword search functionality. Cryptographic primitives such as Symmetric Searchable Encryption (SSE) schemes have been proposed to recover this functionality. However, no SSE construction properly defines correctness and successfully guarantees security in a concurrent setting. This paper attempts a first step in this direction by recommending linearizability as the standard notion of correctness for a concurrent SSE. We study the impact of concurrency on security and stress the need for finer-grained security models. Hence, we propose the log-security model that guarantees security against an adversary having access to persistency-related logs, fixing a blind spot in the snapshot model while capturing security in a concurrent setting. We also build the first concurrent SSE solution proven correct and secure in a concurrent setting, that can be implemented on top of any database. Our scheme proved to be fast thanks to optimal wait-free search operations and sequentially-optimal, lock-free modifications, that both execute under one micro-second per binding, while only incurring a 13.3% storage expansion.

Directed Acyclic Graph (DAG) based BFT protocols balance consensus efforts across different parties and maintain high throughput even when some designated parties fail. However, existing DAG-based BFT protocols exhibit long latency to commit decisions, primarily because they have a \emph{leader} every 2 or more ``rounds''. Recent works, such as Shoal (FC'23) and Mysticeti, have deemed supporting a leader vertex in each round particularly difficult, if not impossible. Consequently, even under honest leaders, these protocols require high latency (or communication complexity) to commit the proposal submitted by the leader (leader vertex) and additional latency to commit other proposals (non-leader vertices). In this work, we present Sailfish, the first DAG-based BFT that supports a leader vertex in each round. Under honest leaders, Sailfish maintains a commit latency of one reliable broadcast (RBC) round plus $1\delta$ to commit the leader vertex (where $\delta$ is the actual transmission latency of a message) and only an additional RBC round to commit non-leader vertices. We also extend Sailfish to Multi-leader Sailfish, which facilitates multiple leaders within a single round and commits all leader vertices in a round with a latency of one RBC round plus $1\delta$. Our experimental evaluation demonstrates that our protocols introduce significantly lower latency overhead compared to existing DAG-based protocols, with similar throughput.

Structure-Aware Private Set Intersection (sa-PSI), recently introduced by Garimella et al. (Crypto'22), is a PSI variant where Alice's input set $S_A$ has a publicly known structure (for example, interval, ball or union of balls) and Bob's input $S_B$ is an unstructured set of elements. Prior work achieves sa-PSI where the communication cost only scales with the description size of $S_A$ instead of the set cardinality. However, the computation cost remains linear in the cardinality of $S_A$, which could be prohibitively large. In this work, we present a new semi-honest sa-PSI framework where both computation and communication costs only scale with the description size of $S_A$. Our main building block is a new primitive that we introduce called Incremental Boolean Function Secret Sharing (ibFSS), which is a generalization of FSS that additionally allows for evaluation on input prefixes. We formalize definitions and construct a weak ibFSS for a $d$-dimensional ball with $\ell_\infty$ norm, which may be of independent interest. Independently, we improve spatial hashing techniques (from prior work) when $S_A$ has structure union of $d$-dimensional balls in $(\{0,1\}^u)^d$, each of diameter $\delta$, from $O(u \cdot d \cdot (\log \delta)^d)$ to $O(\log \delta \cdot d)$ in terms of both computation and communication. Finally, we resolve the following open questions from prior work with communication and computation scaling with the description size of the structured set. - Our PSI framework can handle a union of overlapping structures, while prior work strictly requires a disjoint union. - We have a new construction that enables Bob with unstructured input $S_B$ to learn the intersection. - We extend to a richer class of functionalities like structure-aware PSI Cardinality and PSI-Sum of associated values.

Functional bootstrapping in FHE schemes such as FHEW and TFHE allows the evaluation of a function on an encrypted message, in addition to noise reduction. Implementing programs that directly use functional bootstrapping is challenging and error-prone. In this paper, we propose a heuristic that automatically maps Boolean circuits to functional bootstrapping instructions. Unlike other approaches, our method does not limit the encrypted data plaintext space to a power-of-two size, allowing the instantiation of functional bootstrapping with smaller parameters. Furthermore, the negacyclic property of functional bootstrapping is exploited to extend the plaintext space. Despite the inherently greedy nature of the heuristic, experimental results show that the mapped circuits exhibit a significant reduction in evaluation time. Our heuristic demonstrates a $45\%$ reduction in evaluation time when compared to hand-optimized Trivium and Kreyvium implementations.

FAPI 2.0 is a suite of Web protocols developed by the OpenID Foundation's FAPI Working Group (FAPI WG) for third-party data sharing and digital identity in high-risk environments. Even though the specifications are not completely finished, several important entities have started to adopt the FAPI 2.0 protocols, including Norway's national HelseID, Australia's Consumer Data Standards, as well as private companies like Authlete and Australia-based connectID; the predecessor FAPI 1.0 is in widespread use with millions of users. The FAPI WG asked us to accompany the standardization of the FAPI 2.0 protocols with a formal security analysis to proactively identify vulnerabilities before widespread deployment and to provide formal security guarantees for the standards. In this paper, we report on our analysis and findings. Our analysis is based on a detailed model of the Web infrastructure, the so-called Web Infrastructure Model (WIM), which we extend to be able to carry out our analysis of the FAPI 2.0 protocols including important extensions like FAPI-CIBA. Based on the (extended) WIM and formalizations of the security goals and attacker model laid out in the FAPI 2.0 specifications, we provide a formal model of the protocols and carry out a formal security analysis, revealing several attacks. We have worked with the FAPI WG to fix the protocols, resulting in several amendments to the specifications. With these changes in place, we have adjusted our protocol model and formally proved that the security properties hold true under the strong attacker model defined by the FAPI WG.