ALOHA: an architectural-aware framework for deep learning at the edge. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Bernhard Moser 001; Natalia Shepeleva; Francesco Conti 001; Luca Benini; Oscar Ripolles; David Solans; Maura Pintor; et al. (INTESA@ESWEEK, 2018)

Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Maura Pintor; Battista Biggio; Oscar Ripolles; David Solans; Francesco Conti 001; Luca Benini; Todor P. Stefanov; et al. (ICM, 2018)

Be Right Beach: A Social IoT System for Sustainable Tourism Based on Beach Overcrowding Avoidance. - Roberto Girau; Enrico Ferrara; Maura Pintor; Mariella Sole; Daniele D. Giusto (iThings/GreenCom/CPSCom/SmartData, 2018)

On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks. - Ambra Demontis; Marco Melis; Maura Pintor; Matthew Jagielski; Battista Biggio; Alina Oprea; Cristina Nita-Rotaru; Fabio Roli (CoRR, 2018)

Optimization and deployment of CNNs at the edge: the ALOHA experience. - Paolo Meloni; Daniela Loi; Paola Busia; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Todor P. Stefanov; Svetlana Minakova; Francesco Conti 001; Luca Benini; Maura Pintor; Battista Biggio; et al. (CF, 2019)

Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks. - Ambra Demontis; Marco Melis; Maura Pintor; Matthew Jagielski; Battista Biggio; Alina Oprea; Cristina Nita-Rotaru; Fabio Roli (USENIX Security Symposium, 2019)

secml: A Python Library for Secure and Explainable Machine Learning. - Marco Melis; Ambra Demontis; Maura Pintor; Angelo Sotgiu; Battista Biggio (CoRR, 2019)

Detecting Anomalies from Video-Sequences: a Novel Descriptor. - Giulia Orrù; Davide Ghiani; Maura Pintor; Gian Luca Marcialis; Fabio Roli (ICPR, 2020)

Task-Specific Automation in Deep Learning Processes. - 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; et al. (DEXA Workshops, 2021)

Slope: A First-order Approach for Measuring Gradient Obfuscation. - Maura Pintor; Luca Demetrio; Giovanni Manca; Battista Biggio; Fabio Roli (ESANN, 2021)

Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. - Maura Pintor; Fabio Roli; Wieland Brendel; Battista Biggio (NeurIPS, 2021)

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. - Maura Pintor; Luca Demetrio; Angelo Sotgiu; Giovanni Manca; Ambra Demontis; Nicholas Carlini; Battista Biggio; Fabio Roli (CoRR, 2021)

Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes. - Utku Ozbulak; Maura Pintor; Arnout Van Messem; Wesley De Neve (CoRR, 2021)

Explainability-based Debugging of Machine Learning for Vulnerability Discovery. - Angelo Sotgiu; Maura Pintor; Battista Biggio (ARES, 2022)

Robust Machine Learning for Malware Detection over Time. - Daniele Angioni; Luca Demetrio; Maura Pintor; Battista Biggio (ITASEC, 2022)

Explaining Machine Learning DGA Detectors from DNS Traffic Data. - Giorgio Piras; Maura Pintor; Luca Demetrio; Battista Biggio (ITASEC, 2022)

Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. - Maura Pintor; Luca Demetrio; Angelo Sotgiu; Ambra Demontis; Nicholas Carlini; Battista Biggio; Fabio Roli (NeurIPS, 2022)

A Survey on Reinforcement Learning Security with Application to Autonomous Driving. - Ambra Demontis; Maura Pintor; Luca Demetrio; Kathrin Grosse; Hsiao-Ying Lin; Chengfang Fang; Battista Biggio; Fabio Roli (CoRR, 2022)

secml: Secure and explainable machine learning in Python. - Maura Pintor; Luca Demetrio; Angelo Sotgiu; Marco Melis; Ambra Demontis; Battista Biggio (SoftwareX, 2022)

Raze to the Ground: Query-Efficient Adversarial HTML Attacks on Machine-Learning Phishing Webpage Detectors. - Biagio Montaruli; Luca Demetrio; Maura Pintor; Luca Compagna; Davide Balzarotti; Battista Biggio (AISec@CCS, 2023)

AISec '23: 16th ACM Workshop on Artificial Intelligence and Security. - Maura Pintor; Florian Simon Tramèr; Xinyun Chen (CCS, 2023)

Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness. - Maura Pintor; Ambra Demontis; Battista Biggio (ESANN, 2023)

Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. - Giorgio Piras; Giuseppe Floris; Raffaele Mura; Luca Scionis; Maura Pintor; Battista Biggio; Ambra Demontis (ESANN, 2023)

Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. - Dario Lazzaro; Antonio Emanuele Cinà; Maura Pintor; Ambra Demontis; Battista Biggio; Fabio Roli; Marcello Pelillo (ICIAP (2), 2023)

Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. - Maura Pintor; Luca Demetrio; Angelo Sotgiu; Hsiao-Ying Lin; Chengfang Fang; Ambra Demontis; Battista Biggio (ICMLC, 2023)

Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. - Giorgio Piras; Maura Pintor; Ambra Demontis; Battista Biggio (ICMLC, 2023)

AI Security and Safety: The PRALab Research Experience. - Ambra Demontis; Maura Pintor; Luca Demetrio; Angelo Sotgiu; Daniele Angioni; Giorgio Piras; Srishti Gupta; Battista Biggio; Fabio Roli (Ital-IA, 2023)

Cybersecurity and AI: The PRALab Research Experience. - Maura Pintor; Giulia Orrù; Davide Maiorca; Ambra Demontis; Luca Demetrio; Gian Luca Marcialis; Battista Biggio; Fabio Roli (Ital-IA, 2023)

The Threat of Offensive AI to Organizations. - Yisroel Mirsky; Ambra Demontis; Jaidip Kotak; Ram Shankar; Gelei Deng; Liu Yang 003; Xiangyu Zhang; Maura Pintor; Wenke Lee; Yuval Elovici; Battista Biggio (Comput. Secur., 2023)

Why adversarial reprogramming works, when it fails, and how to tell the difference. - Yang Zheng; Xiaoyi Feng; Zhaoqiang Xia; Xiaoyue Jiang; Ambra Demontis; Maura Pintor; Battista Biggio; Fabio Roli (Inf. Sci., 2023)

Stateful detection of adversarial reprogramming. - Yang Zheng; Xiaoyi Feng; Zhaoqiang Xia; Xiaoyue Jiang; Maura Pintor; Ambra Demontis; Battista Biggio; Fabio Roli (Inf. Sci., 2023)

ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches. - Maura Pintor; Daniele Angioni; Angelo Sotgiu; Luca Demetrio; Ambra Demontis; Battista Biggio; Fabio Roli (Pattern Recognit., 2023)

AISec '24: 17th ACM Workshop on Artificial Intelligence and Security. - Maura Pintor; Matthew Jagielski; Xinyun Chen (CCS, 2024)

LFPD: Local-Feature-Powered Defense Against Adaptive Backdoor Attacks. - Wei Guo; Ambra Demontis; Maura Pintor; Patrick P. K. Chan; Battista Biggio (ICMLC, 2024)

Data Drift in Android Malware Detection. - Luca Minnei; Hicham Eddoubi; Angelo Sotgiu; Maura Pintor; Ambra Demontis; Battista Biggio (ICMLC, 2024)

σ-zero: Gradient-based Optimization of 𝓁0-norm Adversarial Examples. - Antonio Emanuele Cinà; Francesco Villani; Maura Pintor; Lea Schönherr; Battista Biggio; Marcello Pelillo (CoRR, 2024)

Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. - Zhang Chen; Luca Demetrio; Srishti Gupta; Xiaoyi Feng; Zhaoqiang Xia; Antonio Emanuele Cinà; Maura Pintor; Luca Oneto; Ambra Demontis; Battista Biggio; Fabio Roli (CoRR, 2024)

Rethinking data augmentation for adversarial robustness. - Hamid Eghbal-zadeh; Werner Zellinger; Maura Pintor; Kathrin Grosse; Khaled Koutini; Bernhard Alois Moser; Battista Biggio; Gerhard Widmer (Inf. Sci., 2024)

AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. - Antonio Emanuele Cinà; Jérôme Rony; Maura Pintor; Luca Demetrio; Ambra Demontis; Battista Biggio; Ismail Ben Ayed; Fabio Roli (AAAI, 2025)

CoEvolution: A Comprehensive Trustworthy Framework For Connected Machine Learning And Secure Interconnected AI Solutions. - Antonios Makris; Apostolos P. Fournaris; Anita Aghaie; Ioannis Arakas; Anna Maria Anaxagorou; Ioannis Arapakis; Davide Bacciu; Battista Biggio; Georgios Bouloukakis; Stavros Bouras; Arne Bröring; Antonio Carta; et al. (CSR, 2025)

σ-zero: Gradient-based Optimization of ℓ0-norm Adversarial Examples. - Antonio Emanuele Cinà; Francesco Villani; Maura Pintor; Lea Schönherr; Battista Biggio; Marcello Pelillo (ICLR, 2025)

Understanding Regression in Continual Learning for Malware Detection. - Daniele Ghiani; Daniele Angioni; Angelo Sotgiu; Maura Pintor; Battista Biggio (ITASEC/SERICS, 2025)

An Experimental Analysis of Semi-supervised Learning for Malware Detection. - Luca Minnei; Giorgio Piras; Angelo Sotgiu; Maura Pintor; Ambra Demontis; Davide Maiorca; Battista Biggio (ITASEC/SERICS, 2025)

HO-FMN: Hyperparameter optimization for fast minimum-norm attacks. - Raffaele Mura; Giuseppe Floris; Luca Scionis; Giorgio Piras; Maura Pintor; Ambra Demontis; Giorgio Giacinto; Battista Biggio; Fabio Roli (Neurocomputing, 2025)

Adversarial pruning: A survey and benchmark of pruning methods for adversarial robustness. - Giorgio Piras; Maura Pintor; Ambra Demontis; Battista Biggio; Giorgio Giacinto; Fabio Roli (Pattern Recognit., 2025)

Buffer-free Class-Incremental Learning with Out-of-Distribution Detection. - Srishti Gupta; Daniele Angioni; Maura Pintor; Ambra Demontis; Lea Schönherr; Battista Biggio; Fabio Roli (CoRR, 2025)

RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image Detectors. - Hicham Eddoubi; Jonas Ricker; Federico Cocchi; Lorenzo Baraldi 001; Angelo Sotgiu; Maura Pintor; Marcella Cornia; Lorenzo Baraldi 002; Asja Fischer; Rita Cucchiara; Battista Biggio (CoRR, 2025)

Evaluating the Evaluators: Trust in Adversarial Robustness Tests. - Antonio Emanuele Cinà; Maura Pintor; Luca Demetrio; Ambra Demontis; Battista Biggio; Fabio Roli (CoRR, 2025)

Regression-aware Continual Learning for Android Malware Detection. - Daniele Ghiani; Daniele Angioni; Giorgio Piras; Angelo Sotgiu; Luca Minnei; Srishti Gupta; Maura Pintor; Fabio Roli; Battista Biggio (CoRR, 2025)

Robustness-Congruent Adversarial Training for Secure Machine Learning Model Updates. - Daniele Angioni; Luca Demetrio; Maura Pintor; Luca Oneto; Davide Anguita; Battista Biggio; Fabio Roli (IEEE Trans. Pattern Anal. Mach. Intell., 2025)