Ambra Demontis

86 papers A* 5B 3Misc 4Journal 57Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Buffer-free class-incremental learning with out-of-distribution detection. Pattern Recognit. Srishti Gupta, Daniele Angioni, Maura Pintor, Ambra Demontis, Lea Schönherr, Fabio Roli, Battista Biggio
2025	J	`jnl`	Adversarial pruning: A survey and benchmark of pruning methods for adversarial robustness. Pattern Recognit. Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio, Giorgio Giacinto, Fabio Roli
2025	—	`conf`	An Experimental Analysis of Semi-supervised Learning for Malware Detection. ITASEC/SERICS Luca Minnei, Giorgio Piras, Angelo Sotgiu, Maura Pintor, Ambra Demontis, Davide Maiorca, Battista Biggio
2025	A*	`conf`	AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. AAAI Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Ismail Ben Ayed, Fabio Roli
2025	J	`jnl`	Backdoor learning curves: explaining backdoor poisoning beyond influence functions. Int. J. Mach. Learn. Cybern. Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2025	J	`jnl`	Buffer-free Class-Incremental Learning with Out-of-Distribution Detection. CoRR Srishti Gupta, Daniele Angioni, Maura Pintor, Ambra Demontis, Lea Schönherr, Battista Biggio, Fabio Roli
2025	J	`jnl`	Energy-latency attacks via sponge poisoning. Inf. Sci. Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2025	J	`jnl`	Evaluating the Evaluators: Trust in Adversarial Robustness Tests. CoRR Antonio Emanuele Cinà, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli
2025	—	`conf`	Evaluating the evaluators: trust in adversarial robustness tests. Ital-IA Antonio Emanuele Cinà, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli
2025	J	`jnl`	HO-FMN: Hyperparameter optimization for fast minimum-norm attacks. Neurocomputing Raffaele Mura, Giuseppe Floris, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Giorgio Giacinto, Battista Biggio, Fabio Roli
2025	J	`jnl`	Out-of-Distribution Detection for Continual Learning: Design Principles and Benchmarking. CoRR Srishti Gupta, Riccardo Balia, Daniele Angioni, Fabio Brau, Maura Pintor, Ambra Demontis, Alessandro Sebastian, Salvatore M. Carta, Fabio Roli, Battista Biggio
2025	J	`jnl`	Prototype-Guided Robust Learning against Backdoor Attacks. CoRR Wei Guo, Maura Pintor, Ambra Demontis, Battista Biggio
2025	J	`jnl`	Silent Until Sparse: Backdoor Attacks on Semi-Structured Sparsity. CoRR Wei Guo, Maura Pintor, Ambra Demontis, Battista Biggio
2024	J	`jnl`	A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification. CoRR Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli
2024	J	`jnl`	Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness. CoRR Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio, Giorgio Giacinto, Fabio Roli
2024	J	`jnl`	AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples. CoRR Antonio Emanuele Cinà, Jérôme Rony, Maura Pintor, Luca Demetrio, Ambra Demontis, Battista Biggio, Ismail Ben Ayed, Fabio Roli
2024	Misc	`conf`	Data Drift in Android Malware Detection. ICMLC Luca Minnei, Hicham Eddoubi, Angelo Sotgiu, Maura Pintor, Ambra Demontis, Battista Biggio
2024	J	`jnl`	HO-FMN: Hyperparameter Optimization for Fast Minimum-Norm Attacks. CoRR Raffaele Mura, Giuseppe Floris, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Giorgio Giacinto, Battista Biggio, Fabio Roli
2024	Misc	`conf`	LFPD: Local-Feature-Powered Defense Against Adaptive Backdoor Attacks. ICMLC Wei Guo, Ambra Demontis, Maura Pintor, Patrick P. K. Chan, Battista Biggio
2024	J	`jnl`	Machine Learning Security Against Data Poisoning: Are We There Yet? Computer Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2024	J	`jnl`	Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis. CoRR Zhang Chen, Luca Demetrio, Srishti Gupta, Xiaoyi Feng, Zhaoqiang Xia, Antonio Emanuele Cinà, Maura Pintor, Luca Oneto, Ambra Demontis, Battista Biggio, Fabio Roli
2023	—	`conf`	AI Security and Safety: The PRALab Research Experience. Ital-IA Ambra Demontis, Maura Pintor, Luca Demetrio, Angelo Sotgiu, Daniele Angioni, Giorgio Piras, Srishti Gupta, Battista Biggio, Fabio Roli
2023	—	`conf`	BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability. PAKDD (1) Xinglong Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gillian Dobbie, Jörg Wicker
2023	—	`conf`	Cybersecurity and AI: The PRALab Research Experience. Ital-IA Maura Pintor, Giulia Orrù, Davide Maiorca, Ambra Demontis, Luca Demetrio, Gian Luca Marcialis, Battista Biggio, Fabio Roli
2023	Misc	`conf`	Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. ICMLC Maura Pintor, Luca Demetrio, Angelo Sotgiu, Hsiao-Ying Lin, Chengfang Fang, Ambra Demontis, Battista Biggio
2023	J	`jnl`	Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks. CoRR Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli
2023	J	`jnl`	Hardening RGB-D object recognition systems against adversarial patch attacks. Inf. Sci. Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli
2023	J	`jnl`	ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches. Pattern Recognit. Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli
2023	B	`conf`	Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. ESANN Giorgio Piras, Giuseppe Floris, Raffaele Mura, Luca Scionis, Maura Pintor, Battista Biggio, Ambra Demontis
2023	J	`jnl`	Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization. CoRR Giuseppe Floris, Raffaele Mura, Luca Scionis, Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
2023	—	`conf`	Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. ICIAP (2) Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2023	J	`jnl`	Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training. CoRR Dario Lazzaro, Antonio Emanuele Cinà, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2023	Misc	`conf`	Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. ICMLC Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
2023	J	`jnl`	Samples on Thin Ice: Re-Evaluating Adversarial Pruning of Neural Networks. CoRR Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio
2023	J	`jnl`	Stateful detection of adversarial reprogramming. Inf. Sci. Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
2023	J	`jnl`	The Threat of Offensive AI to Organizations. Comput. Secur. Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Gelei Deng, Liu Yang, Xiangyu Zhang, Maura Pintor, Wenke Lee, Yuval Elovici, Battista Biggio
2023	B	`conf`	Towards Machine Learning Models that We Can Trust: Testing, Improving, and Explaining Robustness. ESANN Maura Pintor, Ambra Demontis, Battista Biggio
2023	J	`jnl`	Why adversarial reprogramming works, when it fails, and how to tell the difference. Inf. Sci. Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli
2023	J	`jnl`	Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. ACM Comput. Surv. Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
2022	J	`jnl`	A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification. IEEE Wirel. Commun. Lett. Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli
2022	J	`jnl`	A Survey on Reinforcement Learning Security with Application to Autonomous Driving. CoRR Ambra Demontis, Maura Pintor, Luca Demetrio, Kathrin Grosse, Hsiao-Ying Lin, Chengfang Fang, Battista Biggio, Fabio Roli
2022	A*	`conf`	AISec '22: 15th ACM Workshop on Artificial Intelligence and Security. CCS Ambra Demontis, Xinyun Chen, Florian Tramèr
2022	J	`jnl`	Do gradient-based explanations tell anything about adversarial robustness to android malware? Int. J. Mach. Learn. Cybern. Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli
2022	J	`jnl`	Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli
2022	J	`jnl`	Energy-Latency Attacks via Sponge Poisoning. CoRR Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2022	J	`jnl`	ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches. CoRR Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli
2022	A*	`conf`	Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. NeurIPS Maura Pintor, Luca Demetrio, Angelo Sotgiu, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli
2022	J	`jnl`	Machine Learning Security against Data Poisoning: Are We There Yet? CoRR Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2022	—	`ed.`	Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security, AISec 2022, Los Angeles, CA, USA, 11 November 2022 AISec@CCS Ambra Demontis, Xinyun Chen, Florian Tramèr
2022	J	`jnl`	Stateful Detection of Adversarial Reprogramming. CoRR Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Maura Pintor, Ambra Demontis, Battista Biggio, Fabio Roli
2022	J	`jnl`	Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. CoRR Antonio Emanuele Cinà, Kathrin Grosse, Ambra Demontis, Sebastiano Vascon, Werner Zellinger, Bernhard Alois Moser, Alina Oprea, Battista Biggio, Marcello Pelillo, Fabio Roli
2022	J	`jnl`	secml: Secure and explainable machine learning in Python. SoftwareX Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio
2021	—	`ed.`	AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, Virtual Event, Republic of Korea, 15 November 2021 AISec@CCS Nicholas Carlini, Ambra Demontis, Yizheng Chen
2021	J	`jnl`	Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions. CoRR Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2021	J	`jnl`	Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples. CoRR Maura Pintor, Luca Demetrio, Angelo Sotgiu, Giovanni Manca, Ambra Demontis, Nicholas Carlini, Battista Biggio, Fabio Roli
2021	J	`jnl`	Intriguing Usage of Applicability Domain: Lessons from Cheminformatics Applied to Adversarial Learning. CoRR Luke Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gill Dobbie, Jörg Wicker
2021	—	`conf`	Session details: Session 2B: Machine Learning for Cybersecurity. AISec@CCS Ambra Demontis
2021	B	`conf`	The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? IJCNN Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2021	J	`jnl`	The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers? CoRR Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
2021	J	`jnl`	The Threat of Offensive AI to Organizations. CoRR Yisroel Mirsky, Ambra Demontis, Jaidip Kotak, Ram Shankar, Gelei Deng, Liu Yang, Xiangyu Zhang, Wenke Lee, Yuval Elovici, Battista Biggio
2021	J	`jnl`	Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference. CoRR Yang Zheng, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Maura Pintor, Battista Biggio, Fabio Roli
2020	A*	`conf`	AISec'20: 13th Workshop on Artificial Intelligence and Security. CCS Sadia Afroz, Nicholas Carlini, Ambra Demontis
2020	J	`jnl`	Adversarial Detection of Flash Malware: Limitations and Open Issues. Comput. Secur. Davide Maiorca, Ambra Demontis, Battista Biggio, Fabio Roli, Giorgio Giacinto
2020	J	`jnl`	Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers? CoRR Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli
2020	J	`jnl`	Deep neural rejection against adversarial examples. EURASIP J. Inf. Secur. Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli
2020	J	`jnl`	Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware? CoRR Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli
2019	J	`jnl`	Deep Neural Rejection against Adversarial Examples. CoRR Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli
2019	A*	`conf`	Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks. USENIX Security Symposium Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli
2019	J	`jnl`	Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. IEEE Trans. Dependable Secur. Comput. Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli
2019	J	`jnl`	secml: A Python Library for Secure and Explainable Machine Learning. CoRR Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio
2018	—	`conf`	Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. EUSIPCO Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli
2018	J	`jnl`	Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. CoRR Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli
2018	J	`jnl`	On the Intriguing Connections of Regularization, Input Gradients and Transferability of Evasion and Poisoning Attacks. CoRR Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli
2018	—	`—`	Securing Machine Learning against Adversarial Attacks. Ambra Demontis
2017	—	`conf`	Infinity-Norm Support Vector Machines Against Adversarial Label Contamination. ITASEC Ambra Demontis, Battista Biggio, Giorgio Fumera, Giorgio Giacinto, Fabio Roli
2017	—	`conf`	Is Deep Learning Safe for Robot Vision? Adversarial Examples Against the iCub Humanoid. ICCV Workshops Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli
2017	J	`jnl`	Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid. CoRR Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli
2017	J	`jnl`	On Security and Sparsity of Linear Classifiers for Adversarial Settings. CoRR Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli
2017	J	`jnl`	Super-sparse Learning in Similarity Spaces. CoRR Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli
2017	—	`conf`	Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. AISec@CCS Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli
2017	J	`jnl`	Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. CoRR Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli
2017	J	`jnl`	Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection. CoRR Ambra Demontis, Marco Melis, Battista Biggio, Davide Maiorca, Daniel Arp, Konrad Rieck, Igino Corona, Giorgio Giacinto, Fabio Roli
2016	—	`conf`	On Security and Sparsity of Linear Classifiers for Adversarial Settings. S+SSPR Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli
2016	—	`conf`	Secure Kernel Machines against Evasion Attacks. AISec@CCS Paolo Russu, Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli
2016	J	`jnl`	Super-Sparse Learning in Similarity Spaces. IEEE Comput. Intell. Mag. Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli
2015	—	`conf`	Super-Sparse Regression for Fast Age Estimation from Faces at Test Time. ICIAP (2) Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli