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ORCIDMaura Pintor
Person information
- affiliation: University of Cagliari, Department of Electrical and Electronic Engineering, Italy
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2020 – today
- 2024
[j6]Hamid Eghbal-zadeh
, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard Alois Moser, Battista Biggio, Gerhard Widmer:
Rethinking data augmentation for adversarial robustness. Inf. Sci. 654: 119838 (2024)- [i22]Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo:
σ-zero: Gradient-based Optimization of 𝓁0-norm Adversarial Examples. CoRR abs/2402.01879 (2024) - [i21]Daniele Angioni, Luca Demetrio, Maura Pintor, Luca Oneto, Davide Anguita, Battista Biggio, Fabio Roli:
Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. CoRR abs/2402.17390 (2024) - [i20]Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Ismail Ben Ayed, Fabio Roli:
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. CoRR abs/2404.19460 (2024) - [i19]Zhang Chen, Luca Demetrio, Srishti Gupta, Xiaoyi Feng, Zhaoqiang Xia, Antonio Emanuele Cinà, Maura Pintor, Luca Oneto, Ambra Demontis, Battista Biggio, Fabio Roli:
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. CoRR abs/2406.10090 (2024) - [i18]Raffaele Mura, Giuseppe Floris, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Giorgio Giacinto, Battista Biggio, Fabio Roli:
HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks. CoRR abs/2407.08806 (2024) - [i17]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio, Giorgio Giacinto, Fabio Roli:
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness. CoRR abs/2409.01249 (2024) - 2023
- [j5]Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Gelei Deng, Liu Yang, Xiangyu Zhang, Maura Pintor, Wenke Lee, Yuval Elovici, Battista Biggio:
The Threat of Offensive AI to Organizations. Comput. Secur. 124: 103006 (2023) - [j4]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli:
Why adversarial reprogramming works, when it fails, and how to tell the difference. Inf. Sci. 632: 130-143 (2023) - [j3]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli:
Stateful detection of adversarial reprogramming. Inf. Sci. 642: 119093 (2023) - [j2]Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli:
ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches. Pattern Recognit. 134: 109064 (2023) - [c22]Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio:
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors. AISec@CCS 2023: 233-244 - [c21]Maura Pintor, Florian Simon Tramèr, Xinyun Chen:
AISec '23: 16th ACM Workshop on Artificial Intelligence and Security. CCS 2023: 3666-3668 - [c20]Maura Pintor, Ambra Demontis, Battista Biggio:
Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness. ESANN 2023 - [c19]Giorgio Piras, Giuseppe Floris, Raffaele Mura, Luca Scionis, Maura Pintor, Battista Biggio, Ambra Demontis:
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. ESANN 2023 - [c18]Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. ICIAP (2) 2023: 515-526 - [c17]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Hsiao-Ying Lin, Chengfang Fang, Ambra Demontis, Battista Biggio:
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. ICMLC 2023: 57-62 - [c16]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. ICMLC 2023: 229-235 - [c15]Ambra Demontis, Maura Pintor, Luca Demetrio, Angelo Sotgiu, Daniele Angioni, Giorgio Piras, Srishti Gupta, Battista Biggio, Fabio Roli:
AI Security and Safety: The PRALab Research Experience. Ital-IA 2023: 324-328 - [c14]Maura Pintor, Giulia Orrù, Davide Maiorca, Ambra Demontis, Luca Demetrio, Gian Luca Marcialis, Battista Biggio, Fabio Roli:
Cybersecurity and AI: The PRALab Research Experience. Ital-IA 2023: 426-431 - [e1]Maura Pintor, Xinyun Chen, Florian Tramèr:
Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, AISec 2023, Copenhagen, Denmark, 30 November 2023. ACM 2023 [contents] - [i16]Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo:
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. CoRR abs/2307.00368 (2023) - [i15]Biagio Montaruli, Luca Demetrio, Maura Pintor, Luca Compagna, Davide Balzarotti, Battista Biggio:
Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors. CoRR abs/2310.03166 (2023) - [i14]Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. CoRR abs/2310.08073 (2023) - [i13]Giuseppe Floris, Raffaele Mura, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio:
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. CoRR abs/2310.08177 (2023) - 2022
- [j1]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio:
secml: Secure and explainable machine learning in Python. SoftwareX 18: 101095 (2022) - [c13]Angelo Sotgiu, Maura Pintor, Battista Biggio:
Explainability-based Debugging of Machine Learning for Vulnerability Discovery. ARES 2022: 113:1-113:8 - [c12]Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio:
Explaining Machine Learning DGA Detectors from DNS Traffic Data. ITASEC 2022: 150-168 - [c11]Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio:
Robust Machine Learning for Malware Detection over Time. ITASEC 2022: 169-180 - [c10]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli:
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. NeurIPS 2022 - [i12]Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli:
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches. CoRR abs/2203.04412 (2022) - [i11]Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio:
Robust Machine Learning for Malware Detection over Time. CoRR abs/2208.04838 (2022) - [i10]Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio:
Explaining Machine Learning DGA Detectors from DNS Traffic Data. CoRR abs/2208.05285 (2022) - [i9]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli:
Stateful Detection of Adversarial Reprogramming. CoRR abs/2211.02885 (2022) - [i8]Ambra Demontis, Maura Pintor, Luca Demetrio, Kathrin Grosse, Hsiao-Ying Lin, Chengfang Fang, Battista Biggio, Fabio Roli:
A Survey on Reinforcement Learning Security with Application to Autonomous Driving. CoRR abs/2212.06123 (2022) - 2021
- [c9]Georg Buchgeher, Gerald Czech, Adriano Souza Ribeiro, Werner Kloihofer, Paolo Meloni, Paola Busia, Gianfranco Deriu, Maura Pintor, Battista Biggio, Cristina Chesta, Luca Rinelli, David Solans, Manuel Portela:
Task-Specific Automation in Deep Learning Processes. DEXA Workshops 2021: 159-169 - [c8]Maura Pintor, Luca Demetrio, Giovanni Manca, Battista Biggio, Fabio Roli:
Slope: A First-order Approach for Measuring Gradient Obfuscation. ESANN 2021 - [c7]Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio:
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. NeurIPS 2021: 20052-20062 - [i7]Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio:
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. CoRR abs/2102.12827 (2021) - [i6]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Giovanni Manca, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli:
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. CoRR abs/2106.09947 (2021) - [i5]Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli:
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference. CoRR abs/2108.11673 (2021) - [i4]Utku Ozbulak, Maura Pintor, Arnout Van Messem, Wesley De Neve:
Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes. CoRR abs/2111.11056 (2021) - 2020
- [c6]Giulia Orrù, Davide Ghiani, Maura Pintor, Gian Luca Marcialis, Fabio Roli:
Detecting Anomalies from Video-Sequences: a Novel Descriptor. ICPR 2020: 4642-4649 - [i3]Giulia Orrù, Davide Ghiani, Maura Pintor, Gian Luca Marcialis, Fabio Roli:
Detecting Anomalies from Video-Sequences: a Novel Descriptor. CoRR abs/2010.06407 (2020)
2010 – 2019
- 2019
- [c5]Paolo Meloni, Daniela Loi, Paola Busia, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Todor P. Stefanov, Svetlana Minakova, Francesco Conti, Luca Benini, Maura Pintor, Battista Biggio, Bernhard Moser, Natalia Shepeleva, Nikos Fragoulis, Ilias Theodorakopoulos, Michael Masin, Francesca Palumbo:
Optimization and deployment of CNNs at the edge: the ALOHA experience. CF 2019: 326-332 - [c4]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks. USENIX Security Symposium 2019: 321-338 - [i2]Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio:
secml: A Python Library for Secure and Explainable Machine Learning. CoRR abs/1912.10013 (2019) - 2018
- [c3]Paolo Meloni, Daniela Loi, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Bernhard Moser, Natalia Shepeleva, Francesco Conti, Luca Benini, Oscar Ripolles, David Solans, Maura Pintor, Battista Biggio, Todor P. Stefanov, Svetlana Minakova, Nikolaos Fragoulis, Ilias Theodorakopoulos, Michael Masin, Francesca Palumbo:
ALOHA: an architectural-aware framework for deep learning at the edge. INTESA@ESWEEK 2018: 19-26 - [c2]Paolo Meloni, Daniela Loi, Gianfranco Deriu, Andy D. Pimentel, Dolly Sapra, Maura Pintor, Battista Biggio, Oscar Ripolles, David Solans, Francesco Conti, Luca Benini, Todor P. Stefanov, Svetlana Minakova, Bernhard Moser, Natalia Shepeleva, Michael Masin, Francesca Palumbo, Nikos Fragoulis, Ilias Theodorakopoulos:
Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. ICM 2018: 52-55 - [c1]Roberto Girau, Enrico Ferrara, Maura Pintor, Mariella Sole, Daniele D. Giusto:
Be Right Beach: A Social IoT System for Sustainable Tourism Based on Beach Overcrowding Avoidance. iThings/GreenCom/CPSCom/SmartData 2018: 9-14 - [i1]Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli:
On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks. CoRR abs/1809.02861 (2018)
Coauthor Index
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