Ambra Demontis

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 67

Top Topics

Linear Classifiers

Workshop On Artificial Intelligence

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)
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)
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)
Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli
A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification. 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)
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)
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)
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)
Xinglong Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gillian Dobbie, Jörg Wicker
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability. PAKDD (1) (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)
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)
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)
Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio
secml: Secure and explainable machine learning in Python. SoftwareX 18 (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)
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)
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)
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)
Lu Zhang, Sangarapillai Lambotharan, Gan Zheng, Guisheng Liao, Ambra Demontis, Fabio Roli
A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification. IEEE Wirel. Commun. Lett. 11 (6) (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)
Ambra Demontis, Xinyun Chen, Florian Tramèr
AISec '22: 15th ACM Workshop on Artificial Intelligence and Security. CCS (2022)
Antonio Emanuele Cinà, Ambra Demontis, Battista Biggio, Fabio Roli, Marcello Pelillo
Energy-Latency Attacks via Sponge Poisoning. CoRR (2022)
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)
Luke Chang, Katharina Dost, Kaiqi Zhao, Ambra Demontis, Fabio Roli, Gill Dobbie, Jörg Wicker
Intriguing Usage of Applicability Domain: Lessons from Cheminformatics Applied to Adversarial Learning. CoRR (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, 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)
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)
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)
Ambra Demontis
Session details: Session 2B: Machine Learning for Cybersecurity. AISec@CCS (2021)
Sadia Afroz, Nicholas Carlini, Ambra Demontis
AISec'20: 13th Workshop on Artificial Intelligence and Security. CCS (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)
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)
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)
Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio
secml: A Python Library for Secure and Explainable Machine Learning. CoRR (2019)
Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli
Deep Neural Rejection against Adversarial Examples. CoRR (2019)
Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. CoRR (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)
Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, Davide Maiorca, Giorgio Giacinto, Claudia Eckert, Fabio Roli
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables. EUSIPCO (2018)
Ambra Demontis, Battista Biggio, Giorgio Fumera, Giorgio Giacinto, Fabio Roli
Infinity-Norm Support Vector Machines Against Adversarial Label Contamination. ITASEC (2017)
Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli
On Security and Sparsity of Linear Classifiers for Adversarial Settings. CoRR (2017)
Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli
Super-sparse Learning in Similarity Spaces. CoRR (2017)
Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli
Is Deep Learning Safe for Robot Vision? Adversarial Examples Against the iCub Humanoid. ICCV Workshops (2017)
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. CoRR (2017)
Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. AISec@CCS (2017)
Marco Melis, Ambra Demontis, Battista Biggio, Gavin Brown, Giorgio Fumera, Fabio Roli
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid. CoRR (2017)
Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C. Lupu, Fabio Roli
Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization. CoRR (2017)
Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Fabio Roli
Super-Sparse Learning in Similarity Spaces. IEEE Comput. Intell. Mag. 11 (4) (2016)
Paolo Russu, Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli
Secure Kernel Machines against Evasion Attacks. AISec@CCS (2016)
Ambra Demontis, Paolo Russu, Battista Biggio, Giorgio Fumera, Fabio Roli
On Security and Sparsity of Linear Classifiers for Adversarial Settings. S+SSPR (2016)
Ambra Demontis, Battista Biggio, Giorgio Fumera, Fabio Roli
Super-Sparse Regression for Fast Age Estimation from Faces at Test Time. ICIAP (2) (2015)