Battista Biggio

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 159

Top Venues

Publications

Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
Machine Learning Security Against Data Poisoning: Are We There Yet? Computer 57 (3) (2024)
Zhishan Li, Hongxu Chen, Battista Biggio, Yifan He, Haoran Cai, Fabio Roli, Lei Xie
Toward Effective Traffic Sign Detection via Two-Stage Fusion Neural Networks. IEEE Trans. Intell. Transp. Syst. 25 (8) (2024)
Daniel Gibert, Luca Demetrio, Giulio Zizzo, Quan Le, Jordi Planes, Battista Biggio
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing. CoRR (2024)
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)
Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli
Living-off-The-Land Reverse-Shell Detection by Informed Data Augmentation. CoRR (2024)
Kathrin Grosse, Lukas Bieringer, Tarek R. Besold, Battista Biggio, Alexandre Alahi
When Your AI Becomes a Target: AI Security Incidents and Best Practices. AAAI (2024)
Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli
Nebula: Self-Attention for Dynamic Malware Analysis. IEEE Trans. Inf. Forensics Secur. 19 (2024)
Christian Scano, Giuseppe Floris, Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio
ModSec-Learn: Boosting ModSecurity with Machine Learning. 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)
Andrea Ponte, Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Ivan Tesfai Ogbu, Fabio Roli
SLIFER: Investigating Performance and Robustness of Malware Detection Pipelines. 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, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli
Hardening RGB-D object recognition systems against adversarial patch attacks. Inf. Sci. 651 (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, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks. CoRR (2023)
Dmitrijs Trizna, Luca Demetrio, Battista Biggio, Fabio Roli
Nebula: Self-Attention for Dynamic Malware Analysis. CoRR (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)
Kathrin Grosse, Lukas Bieringer, Tarek R. Besold, Battista Biggio, Katharina Krombholz
Machine Learning Security in Industry: A Quantitative Survey. IEEE Trans. Inf. Forensics Secur. 18 (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)
Emanuele Ledda, Daniele Angioni, Giorgio Piras, Giorgio Fumera, Battista Biggio, Fabio Roli
Adversarial Attacks Against Uncertainty Quantification. ICCV (Workshops) (2023)
Kathrin Grosse, Lukas Bieringer, Tarek R. Besold, Battista Biggio, Katharina Krombholz
Machine Learning Security in Industry: A Quantitative Survey. IEEE Trans. Instrum. Meas. 72 (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)
Biagio Montaruli, Luca Demetrio, Andrea Valenza, Luca Compagna, Davide Ariu, Luca Piras, Davide Balzarotti, Battista Biggio
Adversarial ModSecurity: Countering Adversarial SQL Injections with Robust Machine Learning. CoRR (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)
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. ACM Comput. Surv. 55 (13s) (2023)
Avishag Shapira, Alon Zolfi, Luca Demetrio, Battista Biggio, Asaf Shabtai
Phantom Sponges: Exploiting Non-Maximum Suppression to Attack Deep Object Detectors. WACV (2023)
Emanuele Ledda, Daniele Angioni, Giorgio Piras, Giorgio Fumera, Battista Biggio, Fabio Roli
Adversarial Attacks Against Uncertainty Quantification. CoRR (2023)
Avishag Shapira, Alon Zolfi, Luca Demetrio, Battista Biggio, Asaf Shabtai
Denial-of-Service Attack on Object Detection Model Using Universal Adversarial Perturbation. CoRR (2022)
Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio
Explaining Machine Learning DGA Detectors from DNS Traffic Data. CoRR (2022)
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. CoRR (2022)
Battista Biggio, Nicholas Carlini, Pavel Laskov, Konrad Rieck, Antonio Emanuele Cinà
Security of Machine Learning (Dagstuhl Seminar 22281). Dagstuhl Reports 12 (7) (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)
Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Kathrin Grosse, Lukas Bieringer, Tarek Richard Besold, Battista Biggio, Katharina Krombholz
"Why do so?" - A Practical Perspective on Machine Learning Security. CoRR (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)
Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli
Do gradient-based explanations tell anything about adversarial robustness to android malware? Int. J. Mach. Learn. Cybern. 13 (1) (2022)
Luca Demetrio, Battista Biggio, Fabio Roli
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. CoRR (2022)
Bernhard Alois Moser, Michal Lewandowski, Somayeh Kargaran, Werner Zellinger, Battista Biggio, Christoph Koutschan
Tessellation-Filtering ReLU Neural Networks. IJCAI (2022)
Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
Machine Learning Security against Data Poisoning: Are We There Yet? CoRR (2022)
Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
Stateful Detection of Adversarial Reprogramming. CoRR (2022)
Luca Demetrio, Battista Biggio, Fabio Roli
Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware. IEEE Secur. Priv. 20 (5) (2022)
Huang Xiao, Battista Biggio, Blaine Nelson, Han Xiao, Claudia Eckert, Fabio Roli
Support Vector Machines under Adversarial Label Contamination. 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)
Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Luca Demetrio, Pietro Bongini, Armando Tacchella, Alessandro Sperduti
Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. Neurocomputing 493 (2022)
Lukas Bieringer, Kathrin Grosse, Michael Backes, Battista Biggio, Katharina Krombholz
Industrial practitioners' mental models of adversarial machine learning. SOUPS @ USENIX Security Symposium (2022)
Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio
FADER: Fast adversarial example rejection. Neurocomputing 470 (2022)
Moshe Kravchik, Luca Demetrio, Battista Biggio, Asaf Shabtai
Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems. Comput. Secur. 122 (2022)
Giorgio Piras, Maura Pintor, Luca Demetrio, Battista Biggio
Explaining Machine Learning DGA Detectors from DNS Traffic Data. ITASEC (2022)
Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
Energy-Latency Attacks via Sponge Poisoning. CoRR (2022)
Kathrin Grosse, Taesung Lee, Battista Biggio, Youngja Park, Michael Backes, Ian M. Molloy
Backdoor smoothing: Demystifying backdoor attacks on deep neural networks. Comput. Secur. 120 (2022)
Luca Oneto, Nicolò Navarin, Battista Biggio, Federico Errica, Alessio Micheli, Franco Scarselli, Monica Bianchini, Alessandro Sperduti
Complex Data: Learning Trustworthily, Automatically, and with Guarantees. ESANN (2021)
Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions. CoRR (2021)
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)
Hsiao-Ying Lin, Battista Biggio
Adversarial Machine Learning: Attacks From Laboratories to the Real World. Computer 54 (5) (2021)
Paul Temple, Gilles Perrouin, Mathieu Acher, Battista Biggio, Jean-Marc Jézéquel, Fabio Roli
Empirical assessment of generating adversarial configurations for software product lines. Empir. Softw. Eng. 26 (1) (2021)
Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? CoRR (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)
Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? IJCNN (2021)
Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando
Functionality-Preserving Black-Box Optimization of Adversarial Windows Malware. IEEE Trans. Inf. Forensics Secur. 16 (2021)
Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Deng Gelei, Liu Yang, Xiangyu Zhang, Wenke Lee, Yuval Elovici, Battista Biggio
The Threat of Offensive AI to Organizations. CoRR (2021)
Maura Pintor, Fabio Roli, Wieland Brendel, Battista Biggio
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints. NeurIPS (2021)
Moshe Kravchik, Battista Biggio, Asaf Shabtai
Poisoning attacks on cyber attack detectors for industrial control systems. SAC (2021)
Luca Demetrio, Scott E. Coull, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection. ACM Trans. Priv. Secur. 24 (4) (2021)
Luca Demetrio, Battista Biggio
secml-malware: A Python Library for Adversarial Robustness Evaluation of Windows Malware Classifiers. CoRR (2021)
Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando
Efficient Black-box Optimization of Adversarial Windows Malware with Constrained Manipulations. CoRR (2020)
Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware? CoRR (2020)
Davide Maiorca, Ambra Demontis, Battista Biggio, Fabio Roli, Giorgio Giacinto
Adversarial Detection of Flash Malware: Limitations and Open Issues. Comput. Secur. 96 (2020)
Moshe Kravchik, Battista Biggio, Asaf Shabtai
Poisoning Attacks on Cyber Attack Detectors for Industrial Control Systems. CoRR (2020)
David Solans, Battista Biggio, Carlos Castillo
Poisoning Attacks on Algorithmic Fairness. ECML/PKDD (1) (2020)
David Solans, Battista Biggio, Carlos Castillo
Poisoning Attacks on Algorithmic Fairness. CoRR (2020)
Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli
Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers? CoRR (2020)
Fei Zhang, Patrick P. K. Chan, Battista Biggio, Daniel S. Yeung, Fabio Roli
Adversarial Feature Selection against Evasion Attacks. CoRR (2020)
Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio
FADER: Fast Adversarial Example Rejection. CoRR (2020)
Luca Demetrio, Scott E. Coull, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli
Adversarial EXEmples: A Survey and Experimental Evaluation of Practical Attacks on Machine Learning for Windows Malware Detection. CoRR (2020)
Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli
Deep neural rejection against adversarial examples. EURASIP J. Inf. Secur. 2020 (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)
Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. IEEE Trans. Dependable Secur. Comput. 16 (4) (2019)
Luca Demetrio, Battista Biggio, Giovanni Lagorio, Fabio Roli, Alessandro Armando
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries. CoRR (2019)
Davide Maiorca, Battista Biggio
Digital Investigation of PDF Files: Unveiling Traces of Embedded Malware. IEEE Secur. Priv. 17 (1) (2019)
Davide Maiorca, Battista Biggio, Giorgio Giacinto
Towards Adversarial Malware Detection: Lessons Learned from PDF-based Attacks. ACM Comput. Surv. 52 (4) (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Battista Biggio