Università degli Studi di Cagliari
Maria Infusino
Buffer-free class-incremental learning with out-of-distribution detection
2026-01-01 Gupta, Srishti; Angioni, Daniele; Pintor, Maura; Demontis, Ambra; Schönherr, Lea; Roli, Fabio; Biggio, Battista
An Experimental Analysis of Semi-supervised Learning for Malware Detection
2025-01-01 Minnei, Luca; Piras, Giorgio; Sotgiu, Angelo; Pintor, Maura; Demontis, Ambra; Maiorca, Davide; Biggio, Battista
Data drift in Android malware detection
2025-01-01 Minnei, Luca; Eddoubi, Hicham; Sotgiu, Angelo; Pintor, Maura; Demontis, Ambra; Biggio, Battista
LFPD: Local-Feature-Powered Defense against adaptive backdoor attacks
2025-01-01 Guo, Wei; Demontis, Ambra; Pintor, Maura; Chan, Patrick P. K.; Biggio, Battista
Energy-latency attacks via sponge poisoning
2025-01-01 Cinà, Antonio Emanuele; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
2025-01-01 Cinà, Antonio Emanuele; Rony, Jérôme; Pintor, Maura; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Ayed, Ismail Ben; Roli, Fabio
Adversarial pruning: A survey and benchmark of pruning methods for adversarial robustness
2025-01-01 Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Giacinto, Giorgio; Roli, Fabio
HO-FMN: Hyperparameter optimization for fast minimum-norm attacks
2025-01-01 Mura, Raffaele; Floris, Giuseppe; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Giacinto, Giorgio; Biggio, Battista; Roli, Fabio
Machine Learning Security Against Data Poisoning: Are We There Yet?
2024-01-01 Cinà, Antonio Emanuele; Grosse, Kathrin; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
2024-01-01 Cinà, A. E.; Grosse, K.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M.
The Threat of Offensive AI to Organizations
2023-01-01 Mirsky, Y.; Demontis, A.; Kotak, J.; Shankar, R.; Gelei, D.; Yang, L.; Zhang, X.; Pintor, M.; Lee, W.; Elovici, Y.; Biggio, B.
AI Security and Safety: The PRALab Research Experience
2023-01-01 Demontis, Ambra; Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Angioni, Daniele; Piras, Giorgio; Gupta, Srishti; Biggio, Battista; Roli, Fabio
Hardening RGB-D object recognition systems against adversarial patch attacks
2023-01-01 Zheng, Yang; Demetrio, Luca; Cinà, Antonio Emanuele; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Stateful detection of adversarial reprogramming
2023-01-01 Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Why adversarial reprogramming works, when it fails, and how to tell the difference
2023-01-01 Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Pintor, Maura; Biggio, Battista; Roli, Fabio
Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks
2023-01-01 Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving
2023-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Lin, HSIAO-YING; Fang, Chengfang; Demontis, Ambra; Biggio, Battista
Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization
2023-01-01 Floris, Giuseppe; Mura, Raffaele; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista
BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability
2023-01-01 Chang, X.; Dost, K.; Zhao, K.; Demontis, A.; Roli, F.; Dobbie, G.; Wicker, J.
Cybersecurity and AI: The PRALab Research Experience
2023-01-01 Pintor, Maura; Orru, Giulia; Maiorca, Davide; Demontis, Ambra; Demetrio, Luca; Marcialis, GIAN LUCA; Biggio, Battista; Roli, Fabio
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
2023-01-01 Emanuele Cinà, Antonio; Grosse, Kathrin; Demontis, Ambra; Vascon, Sebastiano; Zellinger, Werner; Moser, Bernhard A.; Oprea, Alina; Biggio, Battista; Pelillo, Marcello; Roli, Fabio
ImageNet-Patch: a dataset for benchmarking machine learning robustness against adversarial patches
2023-01-01 Pintor, Maura; Angioni, Daniele; Sotgiu, Angelo; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Roli, Fabio
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training
2023-01-01 Lazzaro, Dario; Cinà, Antonio Emanuele; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello
Do gradient-based explanations tell anything about adversarial robustness to android malware?
2022-01-01 Melis, M.; Scalas, M.; Demontis, A.; Maiorca, D.; Biggio, B.; Giacinto, G.; Roli, F.
secml: Secure and explainable machine learning in Python
2022-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista
A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification
2022-01-01 Zhang, L; Lambotharan, S; Zheng, G; Liao, Gs; Demontis, A; Roli, F
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
2022-01-01 Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Demontis, Ambra; Carlini, Nicholas; Biggio, Battista; Roli, Fabio
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers
2022-01-01 Melacci, S.; Ciravegna, G.; Sotgiu, A.; Demontis, A.; Biggio, B.; Gori, M.; Roli, F.
The hammer and the nut: is bilevel optimization really needed to poison linear classifiers?
2021-01-01 Cina, A. E.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M.
Adversarial detection of Flash Malware: limitations and Open issues
2020-01-01 Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G.
Deep neural rejection against adversarial examples
2020-01-01 Sotgiu, Angelo; Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Feng, Xiaoyi; Roli, Fabio
Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection
2019-01-01 Demontis, Ambra; Melis, Marco; Biggio, Battista; Maiorca, Davide; Arp, Daniel; Rieck, Konrad; Corona, Igino; Giacinto, Giorgio; Roli, Fabio
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
2019-01-01 Demontis, Ambra; Melis, Marco; Pintor, Maura; Jagielski, Matthew; Biggio, Battista; Oprea, Alina; Nita-Rotaru, Cristina; Roli, Fabio
Securing Machine Learning against Adversarial Attacks
2018-03-26
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables
2018-01-01 Kolosnjaji, Bojan; Demontis, Ambra; Biggio, Battista; Maiorca, Davide; Giacinto, Giorgio; Eckert, Claudia; Roli, Fabio
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid
2018-01-01 Melis, Marco; Demontis, Ambra; Biggio, Battista; Brown, Gavin; Fumera, Giorgio; Roli, Fabio
Infinity-norm support vector machines against adversarial label contamination
2017-01-01 Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Giacinto, Giorgio; Roli, Fabio
Towards poisoning of deep learning algorithms with back-gradient optimization
2017-01-01 Muñoz-González, Luis; Biggio, Battista; Demontis, Ambra; Paudice, Andrea; Wongrassamee, Vasin; Lupu, Emil C.; Roli, Fabio
Secure Kernel Machines against Evasion Attacks
2016-01-01 Russu, Paolo; Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
Super-Sparse Learning in Similarity Spaces
2016-01-01 Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
On security and sparsity of linear classifiers for adversarial settings
2016-01-01 Demontis, Ambra; Russu, Paolo; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
Super-Sparse regression for fast age estimation from faces at test time
2015-01-01 Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio
| Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
|---|---|---|---|---|
| Buffer-free class-incremental learning with out-of-distribution detection | 1-gen-2026 | Gupta, Srishti; Angioni, Daniele; Pintor, Maura; Demontis, Ambra; Schönherr, Lea; Roli, Fabio; Biggio, Battista | PATTERN RECOGNITION | - |
| An Experimental Analysis of Semi-supervised Learning for Malware Detection | 1-gen-2025 | Minnei, Luca; Piras, Giorgio; Sotgiu, Angelo; Pintor, Maura; Demontis, Ambra; Maiorca, Davide; Biggio, Battista | - | - |
| Data drift in Android malware detection | 1-gen-2025 | Minnei, Luca; Eddoubi, Hicham; Sotgiu, Angelo; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | IEEE Computer Society |
| LFPD: Local-Feature-Powered Defense against adaptive backdoor attacks | 1-gen-2025 | Guo, Wei; Demontis, Ambra; Pintor, Maura; Chan, Patrick P. K.; Biggio, Battista | - | IEEE Computer Society |
| Energy-latency attacks via sponge poisoning | 1-gen-2025 | Cinà, Antonio Emanuele; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello | INFORMATION SCIENCES | - |
| AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples | 1-gen-2025 | Cinà, Antonio Emanuele; Rony, Jérôme; Pintor, Maura; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Ayed, Ismail Ben; Roli, Fabio | - | - |
| Adversarial pruning: A survey and benchmark of pruning methods for adversarial robustness | 1-gen-2025 | Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Giacinto, Giorgio; Roli, Fabio | PATTERN RECOGNITION | - |
| HO-FMN: Hyperparameter optimization for fast minimum-norm attacks | 1-gen-2025 | Mura, Raffaele; Floris, Giuseppe; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Giacinto, Giorgio; Biggio, Battista; Roli, Fabio | NEUROCOMPUTING | - |
| Machine Learning Security Against Data Poisoning: Are We There Yet? | 1-gen-2024 | Cinà, Antonio Emanuele; Grosse, Kathrin; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello | COMPUTER | - |
| Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions | 1-gen-2024 | Cinà, A. E.; Grosse, K.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M. | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | - |
| The Threat of Offensive AI to Organizations | 1-gen-2023 | Mirsky, Y.; Demontis, A.; Kotak, J.; Shankar, R.; Gelei, D.; Yang, L.; Zhang, X.; Pintor, M.; Lee, W.; Elovici, Y.; Biggio, B. | COMPUTERS & SECURITY | - |
| AI Security and Safety: The PRALab Research Experience | 1-gen-2023 | Demontis, Ambra; Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Angioni, Daniele; Piras, Giorgio; Gupta, Srishti; Biggio, Battista; Roli, Fabio | - | CEUR-WS Team, Redaktion Sun SITE |
| Hardening RGB-D object recognition systems against adversarial patch attacks | 1-gen-2023 | Zheng, Yang; Demetrio, Luca; Cinà, Antonio Emanuele; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| Stateful detection of adversarial reprogramming | 1-gen-2023 | Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| Why adversarial reprogramming works, when it fails, and how to tell the difference | 1-gen-2023 | Zheng, Yang; Feng, Xiaoyi; Xia, Zhaoqiang; Jiang, Xiaoyue; Demontis, Ambra; Pintor, Maura; Biggio, Battista; Roli, Fabio | INFORMATION SCIENCES | - |
| Samples on Thin Ice: Re-evaluating Adversarial Pruning of Neural Networks | 1-gen-2023 | Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | - |
| Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving | 1-gen-2023 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Lin, HSIAO-YING; Fang, Chengfang; Demontis, Ambra; Biggio, Battista | - | - |
| Improving Fast Minimum-Norm Attacks with Hyperparameter Optimization | 1-gen-2023 | Floris, Giuseppe; Mura, Raffaele; Scionis, Luca; Piras, Giorgio; Pintor, Maura; Demontis, Ambra; Biggio, Battista | - | Ciaco - i6doc.com |
| BAARD: Blocking Adversarial Examples by Testing for Applicability, Reliability and Decidability | 1-gen-2023 | Chang, X.; Dost, K.; Zhao, K.; Demontis, A.; Roli, F.; Dobbie, G.; Wicker, J. | - | SPRINGER INTERNATIONAL PUBLISHING AG |
| Cybersecurity and AI: The PRALab Research Experience | 1-gen-2023 | Pintor, Maura; Orru, Giulia; Maiorca, Davide; Demontis, Ambra; Demetrio, Luca; Marcialis, GIAN LUCA; Biggio, Battista; Roli, Fabio | - | CEUR-WS Team, Redaktion Sun SITE |
| Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning | 1-gen-2023 | Emanuele Cinà, Antonio; Grosse, Kathrin; Demontis, Ambra; Vascon, Sebastiano; Zellinger, Werner; Moser, Bernhard A.; Oprea, Alina; Biggio, Battista; Pelillo, Marcello; Roli, Fabio | ACM COMPUTING SURVEYS | - |
| ImageNet-Patch: a dataset for benchmarking machine learning robustness against adversarial patches | 1-gen-2023 | Pintor, Maura; Angioni, Daniele; Sotgiu, Angelo; Demetrio, Luca; Demontis, Ambra; Biggio, Battista; Roli, Fabio | PATTERN RECOGNITION | - |
| Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training | 1-gen-2023 | Lazzaro, Dario; Cinà, Antonio Emanuele; Pintor, Maura; Demontis, Ambra; Biggio, Battista; Roli, Fabio; Pelillo, Marcello | - | - |
| Do gradient-based explanations tell anything about adversarial robustness to android malware? | 1-gen-2022 | Melis, M.; Scalas, M.; Demontis, A.; Maiorca, D.; Biggio, B.; Giacinto, G.; Roli, F. | INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | - |
| secml: Secure and explainable machine learning in Python | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Melis, Marco; Demontis, Ambra; Biggio, Battista | SOFTWAREX | - |
| A Hybrid Training-Time and Run-Time Defense Against Adversarial Attacks in Modulation Classification | 1-gen-2022 | Zhang, L; Lambotharan, S; Zheng, G; Liao, Gs; Demontis, A; Roli, F | IEEE WIRELESS COMMUNICATIONS LETTERS | - |
| Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples | 1-gen-2022 | Pintor, Maura; Demetrio, Luca; Sotgiu, Angelo; Demontis, Ambra; Carlini, Nicholas; Biggio, Battista; Roli, Fabio | - | Neural information processing systems foundation |
| Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers | 1-gen-2022 | Melacci, S.; Ciravegna, G.; Sotgiu, A.; Demontis, A.; Biggio, B.; Gori, M.; Roli, F. | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
| The hammer and the nut: is bilevel optimization really needed to poison linear classifiers? | 1-gen-2021 | Cina, A. E.; Vascon, S.; Demontis, A.; Biggio, B.; Roli, F.; Pelillo, M. | - | IEEE, Institute of Electrical and Electronics Engineers |
| Adversarial detection of Flash Malware: limitations and Open issues | 1-gen-2020 | Maiorca, D.; Demontis, A.; Biggio, B.; Roli, F.; Giacinto, G. | COMPUTERS & SECURITY | - |
| Deep neural rejection against adversarial examples | 1-gen-2020 | Sotgiu, Angelo; Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Feng, Xiaoyi; Roli, Fabio | EURASIP JOURNAL ON MULTIMEDIA AND INFORMATION SECURITY | - |
| Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection | 1-gen-2019 | Demontis, Ambra; Melis, Marco; Biggio, Battista; Maiorca, Davide; Arp, Daniel; Rieck, Konrad; Corona, Igino; Giacinto, Giorgio; Roli, Fabio | IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING | - |
| Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks | 1-gen-2019 | Demontis, Ambra; Melis, Marco; Pintor, Maura; Jagielski, Matthew; Biggio, Battista; Oprea, Alina; Nita-Rotaru, Cristina; Roli, Fabio | - | USENIX Association |
| Securing Machine Learning against Adversarial Attacks | 26-mar-2018 | - | - | Università degli Studi di Cagliari |
| Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables | 1-gen-2018 | Kolosnjaji, Bojan; Demontis, Ambra; Biggio, Battista; Maiorca, Davide; Giacinto, Giorgio; Eckert, Claudia; Roli, Fabio | - | IEEE (Institute of Electrical and Electronics Engineers) |
| Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid | 1-gen-2018 | Melis, Marco; Demontis, Ambra; Biggio, Battista; Brown, Gavin; Fumera, Giorgio; Roli, Fabio | - | IEEE (Institute of Electrical and Electronics Engineers) |
| Infinity-norm support vector machines against adversarial label contamination | 1-gen-2017 | Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Giacinto, Giorgio; Roli, Fabio | - | CEUR-WS |
| Towards poisoning of deep learning algorithms with back-gradient optimization | 1-gen-2017 | Muñoz-González, Luis; Biggio, Battista; Demontis, Ambra; Paudice, Andrea; Wongrassamee, Vasin; Lupu, Emil C.; Roli, Fabio | - | Association for Computing Machinery |
| Secure Kernel Machines against Evasion Attacks | 1-gen-2016 | Russu, Paolo; Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | - | Association for Computing Machinery |
| Super-Sparse Learning in Similarity Spaces | 1-gen-2016 | Demontis, Ambra; Melis, Marco; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | - |
| On security and sparsity of linear classifiers for adversarial settings | 1-gen-2016 | Demontis, Ambra; Russu, Paolo; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | - | Springer |
| Super-Sparse regression for fast age estimation from faces at test time | 1-gen-2015 | Demontis, Ambra; Biggio, Battista; Fumera, Giorgio; Roli, Fabio | LECTURE NOTES IN COMPUTER SCIENCE | Springer Verlag |
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