Maura Pintor

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 49

Top Topics

Malware Detection

Machine Learning

Autonomous Driving

Top Venues

Publications

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 (2024)
Antonio Emanuele Cinà, Francesco Villani, Maura Pintor, Lea Schönherr, Battista Biggio, Marcello Pelillo
-norm Adversarial Examples. CoRR (2024)
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 (2024)
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 (2024)
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 (2024)
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 (2024)
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 (2023)
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)
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 (2023)
Maura Pintor, Ambra Demontis, Battista Biggio
Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness. ESANN (2023)
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 (2023)
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)
Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
Stateful detection of adversarial reprogramming. Inf. Sci. 642 (2023)
Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. CoRR (2023)
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)
Maura Pintor, Florian Simon Tramèr, Xinyun Chen
AISec '23: 16th ACM Workshop on Artificial Intelligence and Security. CCS (2023)
Giorgio Piras, Giuseppe Floris, Raffaele Mura, Luca Scionis, Maura Pintor, Battista Biggio, Ambra Demontis
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. ESANN (2023)
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 (2023)
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Deng Gelei, Liu Yang, Xiangyu Zhang, Maura Pintor, Wenke Lee, Yuval Elovici, Battista Biggio
The Threat of Offensive AI to Organizations. Comput. Secur. 124 (2023)
Giuseppe Floris, Raffaele Mura, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. CoRR (2023)
Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. ICMLC (2023)
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)
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)
Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio
Explaining Machine Learning DGA Detectors from DNS Traffic Data. CoRR (2022)
Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio
secml: Secure and explainable machine learning in Python. SoftwareX 18 (2022)
Angelo Sotgiu, Maura Pintor, Battista Biggio
Explainability-based Debugging of Machine Learning for Vulnerability Discovery. ARES (2022)
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)
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 (2022)
Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio
Robust Machine Learning for Malware Detection over Time. ITASEC (2022)
Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
Stateful Detection of Adversarial Reprogramming. CoRR (2022)
Daniele Angioni, Luca Demetrio, Maura Pintor, Battista Biggio
Robust Machine Learning for Malware Detection over Time. CoRR (2022)
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 (2022)
Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio
Explaining Machine Learning DGA Detectors from DNS Traffic Data. ITASEC (2022)
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)
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 (2021)
Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. CoRR (2021)
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 (2021)
Maura Pintor, Luca Demetrio, Giovanni Manca, Battista Biggio, Fabio Roli
Slope: A First-order Approach for Measuring Gradient Obfuscation. ESANN (2021)
Utku Ozbulak, Maura Pintor, Arnout Van Messem, Wesley De Neve
Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes. CoRR (2021)
Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. NeurIPS (2021)
Giulia Orrù, Davide Ghiani, Maura Pintor, Gian Luca Marcialis, Fabio Roli
Detecting Anomalies from Video-Sequences: a Novel Descriptor. ICPR (2020)
Giulia Orrù, Davide Ghiani, Maura Pintor, Gian Luca Marcialis, Fabio Roli
Detecting Anomalies from Video-Sequences: a Novel Descriptor. CoRR (2020)
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)
Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio
secml: A Python Library for Secure and Explainable Machine Learning. CoRR (2019)
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)
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)
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)
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)
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 (2018)