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Maura 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) - [i21]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) - [i20]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) - [i19]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) - [i18]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) - [i17]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) - 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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