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2020 – today
- 2024
[j26]Jaromír Janisch
, Tomás Pevný, Viliam Lisý:
Classification with costly features in hierarchical deep sets. Mach. Learn. 113(7): 4487-4522 (2024)- [j25]Vít Skvára, Václav Smídl, Tomás Pevný:
Anomaly detection in multifactor data. Neural Comput. Appl. 36(34): 21561-21580 (2024) - [j24]Michaela Masková, Matej Zorek, Tomás Pevný, Václav Smídl:
Deep anomaly detection on set data: Survey and comparison. Pattern Recognit. 151: 110381 (2024) - [j23]Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer:
Malicious Internet Entity Detection Using Local Graph Inference. IEEE Trans. Inf. Forensics Secur. 19: 3554-3566 (2024) - [j22]Florian Merkle, Maximilian Samsinger, Pascal Schöttle, Tomás Pevný:
On the Economics of Adversarial Machine Learning. IEEE Trans. Inf. Forensics Secur. 19: 4670-4685 (2024) - [c55]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs. ICLR 2024 - [i37]Jiri Nemecek, Tomás Pevný, Jakub Marecek:
Generating Likely Counterfactuals Using Sum-Product Networks. CoRR abs/2401.14086 (2024) - [i36]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Blind Data Adaptation to tackle Covariate Shift in Operational Steganalysis. CoRR abs/2405.16961 (2024) - [i35]Simon Mandlík, Tomás Pevný, Václav Smídl, Lukás Bajer:
Malicious Internet Entity Detection Using Local Graph Inference. CoRR abs/2408.03287 (2024) - [i34]Milan Papez, Martin Rektoris, Tomás Pevný, Václav Smídl:
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs. CoRR abs/2408.07394 (2024) - [i33]Milan Papez, Martin Rektoris, Václav Smídl, Tomás Pevný:
GraphSPNs: Sum-Product Networks Benefit From Canonical Orderings. CoRR abs/2408.09451 (2024) - 2023
- [j21]Quentin Giboulot, Tomás Pevný, Andrew D. Ker:
The Non-Zero-Sum Game of Steganography in Heterogeneous Environments. IEEE Trans. Inf. Forensics Secur. 18: 4436-4448 (2023) - [c54]Leah Chrestien, Tomás Pevný, Stefan Edelkamp, Antonín Komenda:
Heuristic Search Optimisation Using Planning and Curriculum Learning Techniques. EPIA (1) 2023: 495-507 - [c53]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios. ESORICS Workshops (2) 2023: 589-608 - [c52]Leah Chrestien, Stefan Edelkamp, Antonín Komenda, Tomás Pevný:
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal. NeurIPS 2023 - [c51]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Leveraging Data Geometry to Mitigate CSM in Steganalysis. WIFS 2023: 1-6 - [i32]Vít Skvára, Tomás Pevný, Václav Smídl:
Is AUC the best measure for practical comparison of anomaly detectors? CoRR abs/2305.04754 (2023) - [i31]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarios. CoRR abs/2305.17246 (2023) - [i30]Jiri Nemecek, Tomás Pevný, Jakub Marecek:
Improving the Validity of Decision Trees as Explanations. CoRR abs/2306.06777 (2023) - [i29]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Leveraging Data Geometry to Mitigate CSM in Steganalysis. CoRR abs/2310.04479 (2023) - [i28]Leah Chrestien, Tomás Pevný, Stefan Edelkamp, Antonín Komenda:
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal. CoRR abs/2310.19463 (2023) - 2022
- [j20]Simon Mandlík, Matej Racinsky, Viliam Lisý, Tomás Pevný:
JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data. J. Mach. Learn. Res. 23: 298:1-298:5 (2022) - [j19]Lukás Adam, Václav Mácha, Václav Smídl, Tomás Pevný:
General framework for binary classification on top samples. Optim. Methods Softw. 37(5): 1636-1667 (2022) - [j18]Solène Bernard, Patrick Bas, John Klein, Tomás Pevný:
Backpack: A Backpropagable Adversarial Embedding Scheme. IEEE Trans. Inf. Forensics Secur. 17: 3539-3554 (2022) - [j17]Vít Skvára, Jan Francu, Matej Zorek, Tomás Pevný, Václav Smídl:
Comparison of Anomaly Detectors: Context Matters. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2494-2507 (2022) - [c50]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Using Set Covering to Generate Databases for Holistic Steganalysis. WIFS 2022: 1-6 - [i27]Tomás Pevný, Viliam Lisý, Branislav Bosanský, Petr Somol, Michal Pechoucek:
Explaining Classifiers Trained on Raw Hierarchical Multiple-Instance Data. CoRR abs/2208.02694 (2022) - [i26]Leah Chrestien, Tomás Pevný, Antonín Komenda, Stefan Edelkamp:
A Differentiable Loss Function for Learning Heuristics in A. CoRR abs/2209.05206 (2022) - [i25]Rony Abecidan, Vincent Itier, Jérémie Boulanger, Patrick Bas, Tomás Pevný:
Using Set Covering to Generate Databases for Holistic Steganalysis. CoRR abs/2211.03447 (2022) - 2021
- [j16]Solène Bernard, Patrick Bas, John Klein, Tomás Pevný:
Explicit Optimization of min max Steganographic Game. IEEE Trans. Inf. Forensics Secur. 16: 812-823 (2021) - [c49]Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomás Pevný:
When Should You Defend Your Classifier? - - A Game-Theoretical Analysis of Countermeasures Against Adversarial Examples. GameSec 2021: 158-177 - [c48]Solène Bernard, Patrick Bas, Tomás Pevný, John Klein:
Optimizing Additive Approximations of Non-additive Distortion Functions. IH&MMSec 2021: 105-112 - [e3]Dirk Borghys, Patrick Bas, Luisa Verdoliva, Tomás Pevný, Bin Li, Jennifer Newman:
IH&MMSec '21: ACM Workshop on Information Hiding and Multimedia Security, Virtual Event, Belgium, June, 22-25, 2021. ACM 2021, ISBN 978-1-4503-8295-3 [contents] - [i24]Simon Mandlík, Tomás Pevný:
Mapping the Internet: Modelling Entity Interactions in Complex Heterogeneous Networks. CoRR abs/2104.09650 (2021) - [i23]Simon Mandlík, Matej Racinsky, Viliam Lisý, Tomás Pevný:
Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data. CoRR abs/2105.09107 (2021) - [i22]Maximilian Samsinger, Florian Merkle, Pascal Schöttle, Tomás Pevný:
When Should You Defend Your Classifier - A Game-theoretical Analysis of Countermeasures against Adversarial Examples. CoRR abs/2108.07602 (2021) - [i21]Milan Papez, Tomás Pevný, Václav Smídl:
Fitting large mixture models using stochastic component selection. CoRR abs/2110.04776 (2021) - [i20]Leah Chrestien, Tomás Pevný, Antonín Komenda, Stefan Edelkamp:
Heuristic Search Planning with Deep Neural Networks using Imitation, Attention and Curriculum Learning. CoRR abs/2112.01918 (2021) - 2020
- [j15]Martin Kopp, Tomás Pevný, Martin Holena:
Anomaly explanation with random forests. Expert Syst. Appl. 149: 113187 (2020) - [j14]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with costly features as a sequential decision-making problem. Mach. Learn. 109(8): 1587-1615 (2020) - [c47]Marek Dedic, Tomás Pevný, Lukás Bajer, Martin Holena:
Loss Functions for Clustering in Multi-instance Learning. ITAT 2020: 137-146 - [c46]Niklas Heim, Tomás Pevný, Václav Smídl:
Neural Power Units. NeurIPS 2020 - [c45]Tomás Pevný, Václav Smídl, Martin Trapp, Ondrej Polácek, Tomás Oberhuber:
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations. PGM 2020: 341-352 - [e2]Christian Riess, Franziska Schirrmacher, Irene Amerini, Paolo Bestagini, Tomás Pevný:
IH&MMSec '20: ACM Workshop on Information Hiding and Multimedia Security, Denver, CO, USA, June 22-24, 2020. ACM 2020, ISBN 978-1-4503-7050-9 [contents] - [i19]Tomás Pevný, Marek Dedic:
Nested Multiple Instance Learning in Modelling of HTTP network traffic. CoRR abs/2002.04059 (2020) - [i18]Lukás Adam, Václav Mácha, Václav Smídl, Tomás Pevný:
General Framework for Binary Classification on Top Samples. CoRR abs/2002.10923 (2020) - [i17]Tomás Pevný, Václav Smídl, Martin Trapp, Ondrej Polácek, Tomás Oberhuber:
Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations. CoRR abs/2005.01297 (2020) - [i16]Niklas Heim, Tomás Pevný, Václav Smídl:
Neural Power Units. CoRR abs/2006.01681 (2020) - [i15]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks. CoRR abs/2009.12462 (2020) - [i14]Vít Skvára, Jan Francu, Matej Zorek, Tomás Pevný, Václav Smídl:
Comparison of Anomaly Detectors: Context Matters. CoRR abs/2012.06260 (2020)
2010 – 2019
- 2019
- [j13]Paul Prasse, René Knaebel, Lukás Machlica, Tomás Pevný, Tobias Scheffer:
Joint detection of malicious domains and infected clients. Mach. Learn. 108(8-9): 1353-1368 (2019) - [c44]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features Using Deep Reinforcement Learning. AAAI 2019: 3959-3966 - [c43]Solène Bernard, Tomás Pevný, Patrick Bas, John Klein:
Exploiting Adversarial Embeddings for Better Steganography. IH&MMSec 2019: 216-221 - [i13]Václav Smídl, Jan Bím, Tomás Pevný:
Anomaly scores for generative models. CoRR abs/1905.11890 (2019) - [i12]Tomás Pevný, Vojtech Kovarík:
Approximation capability of neural networks on spaces of probability measures and tree-structured domains. CoRR abs/1906.00764 (2019) - [i11]Paul Prasse, René Knaebel, Lukás Machlica, Tomás Pevný, Tobias Scheffer:
Joint Detection of Malicious Domains and Infected Clients. CoRR abs/1906.09084 (2019) - [i10]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features as a Sequential Decision-Making Problem. CoRR abs/1909.02564 (2019) - [i9]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces. CoRR abs/1911.08756 (2019) - [i8]Niklas Heim, Václav Smídl, Tomás Pevný:
Rodent: Relevance determination in ODE. CoRR abs/1912.00656 (2019) - 2018
- [j12]Jan Stiborek, Tomás Pevný, Martin Rehák:
Probabilistic analysis of dynamic malware traces. Comput. Secur. 74: 221-239 (2018) - [j11]Jan Stiborek, Tomás Pevný, Martin Rehák:
Multiple instance learning for malware classification. Expert Syst. Appl. 93: 346-357 (2018) - [j10]Jan Kohout, Tomás Pevný:
Network Traffic Fingerprinting Based on Approximated Kernel Two-Sample Test. IEEE Trans. Inf. Forensics Secur. 13(3): 788-801 (2018) - [c42]Tomás Pevný, Andrew D. Ker:
Exploring Non-Additive Distortion in Steganography. IH&MMSec 2018: 109-114 - [i7]Vyacheslav Kungurtsev, Tomás Pevný:
Algorithms for solving optimization problems arising from deep neural net models: smooth problems. CoRR abs/1807.00172 (2018) - [i6]Vyacheslav Kungurtsev, Tomás Pevný:
Algorithms for solving optimization problems arising from deep neural net models: nonsmooth problems. CoRR abs/1807.00173 (2018) - [i5]Vít Skvára, Tomás Pevný, Václav Smídl:
Are generative deep models for novelty detection truly better? CoRR abs/1807.05027 (2018) - 2017
- [j9]Martin Grill, Tomás Pevný, Martin Rehák:
Reducing false positives of network anomaly detection by local adaptive multivariate smoothing. J. Comput. Syst. Sci. 83(1): 43-57 (2017) - [c41]Karel Durkota, Viliam Lisý, Christopher Kiekintveld, Karel Horák, Branislav Bosanský, Tomás Pevný:
Optimal Strategies for Detecting Data Exfiltration by Internal and External Attackers. GameSec 2017: 171-192 - [c40]Tomás Pevný, Petr Somol:
Using Neural Network Formalism to Solve Multiple-Instance Problems. ISNN (1) 2017: 135-142 - [c39]Paul Prasse, Lukás Machlica, Tomás Pevný, Jirí Havelka, Tobias Scheffer:
Malware Detection by Analysing Encrypted Network Traffic with Neural Networks. ECML/PKDD (2) 2017: 73-88 - [c38]Jakub Lokoc, Tomás Grosup, Premysl Cech, Tomás Pevný, Tomás Skopal:
Malware Discovery Using Behaviour-Based Exploration of Network Traffic. SISAP 2017: 315-323 - [c37]Paul Prasse, Lukás Machlica, Tomás Pevný, Jirí Havelka, Tobias Scheffer:
Malware Detection by Analysing Network Traffic with Neural Networks. IEEE Symposium on Security and Privacy Workshops 2017: 205-210 - [i4]Tomás Pevný, Petr Somol:
Discriminative models for multi-instance problems with tree-structure. CoRR abs/1703.02868 (2017) - [i3]Jan Stiborek, Tomás Pevný, Martin Rehák:
Multiple Instance Learning for Malware Classification. CoRR abs/1705.02268 (2017) - [i2]Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with Costly Features using Deep Reinforcement Learning. CoRR abs/1711.07364 (2017) - 2016
- [j8]Martin Grill, Tomás Pevný:
Learning combination of anomaly detectors for security domain. Comput. Networks 107: 55-63 (2016) - [j7]Jan Jusko, Martin Rehák, Jan Stiborek, Jan Kohout, Tomás Pevný:
Using Behavioral Similarity for Botnet Command-and-Control Discovery. IEEE Intell. Syst. 31(5): 16-22 (2016) - [j6]Tomás Pevný:
Loda: Lightweight on-line detector of anomalies. Mach. Learn. 102(2): 275-304 (2016) - [c36]Tomás Pevný, Petr Somol:
Discriminative Models for Multi-instance Problems with Tree Structure. AISec@CCS 2016: 83-91 - [c35]Andrew D. Ker, Tomás Pevný, Patrick Bas:
Rethinking Optimal Embedding. IH&MMSec 2016: 93-102 - [c34]Tomás Pevný, Martin Kopp, Jakub Kroustek, Andrew D. Ker:
Malicons: Detecting Payload in Favicons. Media Watermarking, Security, and Forensics 2016: 1-9 - [c33]Jakub Lokoc, Jan Kohout, Premysl Cech, Tomás Skopal, Tomás Pevný:
k-NN Classification of Malware in HTTPS Traffic Using the Metric Space Approach. PAISI 2016: 131-145 - [c32]Premysl Cech, Jan Kohout, Jakub Lokoc, Tomás Komárek, Jakub Marousek, Tomás Pevný:
Feature Extraction and Malware Detection on Large HTTPS Data Using MapReduce. SISAP 2016: 311-324 - [c31]Tomás Komárek, Martin Grill, Tomás Pevný:
Passive NAT detection using HTTP access logs. WIFS 2016: 1-6 - [i1]Tomás Pevný, Petr Somol:
Using Neural Network Formalism to Solve Multiple-Instance Problems. CoRR abs/1609.07257 (2016) - 2015
- [c30]Jan Kohout, Tomás Pevný:
Unsupervised detection of malware in persistent web traffic. ICASSP 2015: 1757-1761 - [c29]Jan Kohout, Tomás Pevný:
Automatic discovery of web servers hosting similar applications. IM 2015: 1310-1315 - [c28]Tomás Pevný, Andrew D. Ker:
Towards dependable steganalysis. Media Watermarking, Security, and Forensics 2015: 94090I - [c27]Rémi Cogranne, Vahid Sedighi, Jessica J. Fridrich, Tomás Pevný:
Is ensemble classifier needed for steganalysis in high-dimensional feature spaces? WIFS 2015: 1-6 - [c26]Tomás Pevný, Ivan Nikolaev:
Optimizing pooling function for pooled steganalysis. WIFS 2015: 1-6 - 2014
- [j5]Andrew D. Ker, Tomás Pevný:
The Steganographer is the Outlier: Realistic Large-Scale Steganalysis. IEEE Trans. Inf. Forensics Secur. 9(9): 1424-1435 (2014) - [c25]Tomás Pevný, Andrew D. Ker:
Steganographic key leakage through payload metadata. IH&MMSec 2014: 109-114 - [c24]Andrew D. Ker, Tomás Pevný:
A mishmash of methods for mitigating the model mismatch mess. Media Watermarking, Security, and Forensics 2014: 90280I - [c23]Viliam Lisý, Robert Kessl, Tomás Pevný:
Randomized Operating Point Selection in Adversarial Classification. ECML/PKDD (2) 2014: 240-255 - 2013
- [c22]Tomás Pevný, Martin Komon, Martin Rehák:
Attacking the IDS learning processes. ICASSP 2013: 8687-8691 - [c21]Andrew D. Ker, Patrick Bas, Rainer Böhme, Rémi Cogranne, Scott Craver, Tomás Filler, Jessica J. Fridrich, Tomás Pevný:
Moving steganography and steganalysis from the laboratory into the real world. IH&MMSec 2013: 45-58 - [c20]Tomás Pevný, Andrew D. Ker:
The challenges of rich features in universal steganalysis. Media Watermarking, Security, and Forensics 2013: 86650M - 2012
- [j4]Tomás Pevný, Jessica J. Fridrich, Andrew D. Ker:
From Blind to Quantitative Steganalysis. IEEE Trans. Inf. Forensics Secur. 7(2): 445-454 (2012) - [c19]Andrew D. Ker, Tomás Pevný:
Identifying a steganographer in realistic and heterogeneous data sets. Media Watermarking, Security, and Forensics 2012: 83030N - [c18]Tomás Pevný:
Co-occurrence steganalysis in high dimensions. Media Watermarking, Security, and Forensics 2012: 83030B - [c17]Andrew David Ker, Tomás Pevný:
Batch steganography in the real world. MM&Sec 2012: 1-10 - [c16]Tomás Pevný, Martin Rehák, Martin Grill:
Detecting anomalous network hosts by means of PCA. WIFS 2012: 103-108 - 2011
- [c15]Patrick Bas, Tomás Filler, Tomás Pevný:
"Break Our Steganographic System": The Ins and Outs of Organizing BOSS. Information Hiding 2011: 59-70 - [c14]Andrew D. Ker, Tomás Pevný:
A new paradigm for steganalysis via clustering. Media Forensics and Security 2011: 78800U - [c13]Tomás Pevný:
Detecting messages of unknown length. Media Forensics and Security 2011: 78800T - [e1]Tomás Filler, Tomás Pevný, Scott Craver, Andrew D. Ker:
Information Hiding - 13th International Conference, IH 2011, Prague, Czech Republic, May 18-20, 2011, Revised Selected Papers. Lecture Notes in Computer Science 6958, Springer 2011, ISBN 978-3-642-24177-2 [contents] - 2010
- [j3]Tomás Pevný, Patrick Bas, Jessica J. Fridrich:
Steganalysis by subtractive pixel adjacency matrix. IEEE Trans. Inf. Forensics Secur. 5(2): 215-224 (2010) - [c12]Tomás Pevný, Tomás Filler, Patrick Bas:
Using High-Dimensional Image Models to Perform Highly Undetectable Steganography. Information Hiding 2010: 161-177 - [c11]Jan Kodovský, Tomás Pevný, Jessica J. Fridrich:
Modern steganalysis can detect YASS. Media Forensics and Security 2010: 754102
2000 – 2009
- 2009
- [c10]Tomás Pevný, Jessica J. Fridrich, Andrew D. Ker:
From blind to quantitative steganalysis. Media Forensics and Security 2009: 72540C - [c9]Tomás Pevný, Patrick Bas, Jessica J. Fridrich:
Steganalysis by subtractive pixel adjacency matrix. MM&Sec 2009: 75-84 - 2008
- [j2]Tomás Pevný, Jessica J. Fridrich:
Detection of Double-Compression in JPEG Images for Applications in Steganography. IEEE Trans. Inf. Forensics Secur. 3(2): 247-258 (2008) - [j1]Tomás Pevný, Jessica J. Fridrich:
Multiclass Detector of Current Steganographic Methods for JPEG Format. IEEE Trans. Inf. Forensics Secur. 3(4): 635-650 (2008) - [c8]Tomás Pevný, Jessica J. Fridrich:
Benchmarking for Steganography. Information Hiding 2008: 251-267 - [c7]Andrew D. Ker, Tomás Pevný, Jan Kodovský, Jessica J. Fridrich:
The square root law of steganographic capacity. MM&Sec 2008: 107-116 - [c6]Tomás Pevný, Jessica J. Fridrich:
Novelty detection in blind steganalysis. MM&Sec 2008: 167-176 - [c5]Tomás Pevný, Jessica J. Fridrich:
Estimation of primary quantization matrix for steganalysis of double-compressed JPEG images. Security, Forensics, Steganography, and Watermarking of Multimedia Contents 2008: 681911 - 2007
- [c4]Jessica J. Fridrich, Tomás Pevný, Jan Kodovský:
Statistically undetectable jpeg steganography: dead ends challenges, and opportunities. MM&Sec 2007: 3-14 - [c3]Tomás Pevný, Jessica J. Fridrich:
Merging Markov and DCT features for multi-class JPEG steganalysis. Security, Steganography, and Watermarking of Multimedia Contents 2007: 650503 - 2006
- [c2]Tomás Pevný, Jessica J. Fridrich:
Multi-class blind steganalysis for JPEG images. Security, Steganography, and Watermarking of Multimedia Contents 2006: 60720O - 2005
- [c1]Tomás Pevný, Jessica J. Fridrich:
Towards Multi-class Blind Steganalyzer for JPEG Images. IWDW 2005: 39-53
Coauthor Index
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