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2020 – today
- 2024
[i8]Francesco Villani, Igor Maljkovic, Dario Lazzaro, Angelo Sotgiu, Antonio Emanuele Cinà, Fabio Roli:
Robust image classification with multi-modal large language models. CoRR abs/2412.10353 (2024)- 2023
- [j5]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: 109064 (2023) - [c5]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: 57-62 - [c4]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: 324-328 - 2022
- [j4]Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio:
FADER: Fast adversarial example rejection. Neurocomputing 470: 257-268 (2022) - [j3]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): 9944-9959 (2022) - [j2]Maura Pintor, Luca Demetrio, Angelo Sotgiu, Marco Melis, Ambra Demontis, Battista Biggio:
secml: Secure and explainable machine learning in Python. SoftwareX 18: 101095 (2022) - [c3]Angelo Sotgiu, Maura Pintor, Battista Biggio:
Explainability-based Debugging of Machine Learning for Vulnerability Discovery. ARES 2022: 113:1-113:8 - [c2]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 - [i7]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 abs/2203.04412 (2022) - 2021
- [i6]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 abs/2106.09947 (2021) - 2020
- [j1]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: 5 (2020) - [i5]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 abs/2006.03833 (2020) - [i4]Francesco Crecchi, Marco Melis, Angelo Sotgiu, Davide Bacciu, Battista Biggio:
FADER: Fast Adversarial Example Rejection. CoRR abs/2010.09119 (2020)
2010 – 2019
- 2019
- [i3]Angelo Sotgiu, Ambra Demontis, Marco Melis, Battista Biggio, Giorgio Fumera, Xiaoyi Feng, Fabio Roli:
Deep Neural Rejection against Adversarial Examples. CoRR abs/1910.00470 (2019) - [i2]Marco Melis, Ambra Demontis, Maura Pintor, Angelo Sotgiu, Battista Biggio:
secml: A Python Library for Secure and Explainable Machine Learning. CoRR abs/1912.10013 (2019) - 2018
- [i1]Mansour Ahmadi, Angelo Sotgiu, Giorgio Giacinto:
IntelliAV: Building an Effective On-Device Android Malware Detector. CoRR abs/1802.01185 (2018) - 2017
- [c1]Mansour Ahmadi, Angelo Sotgiu, Giorgio Giacinto:
IntelliAV: Toward the Feasibility of Building Intelligent Anti-malware on Android Devices. CD-MAKE 2017: 137-154
Coauthor Index
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