| Deep neural rejection against adversarial examples A Sotgiu, A Demontis, M Melis, B Biggio, G Fumera, X Feng, F Roli EURASIP Journal on Information Security 2020, 1-10, 2020 | 69 | 2020 |
| secml: Secure and explainable machine learning in Python M Pintor, L Demetrio, A Sotgiu, M Melis, A Demontis, B Biggio SoftwareX 18, 101095, 2022 | 63* | 2022 |
| ImageNet-Patch: A dataset for benchmarking machine learning robustness against adversarial patches M Pintor, D Angioni, A Sotgiu, L Demetrio, A Demontis, B Biggio, F Roli Pattern Recognition 134, 109064, 2023 | 49 | 2023 |
| Indicators of attack failure: Debugging and improving optimization of adversarial examples M Pintor, L Demetrio, A Sotgiu, A Demontis, N Carlini, B Biggio, F Roli Advances in Neural Information Processing Systems 35, 23063-23076, 2022 | 38 | 2022 |
| Domain knowledge alleviates adversarial attacks in multi-label classifiers S Melacci, G Ciravegna, A Sotgiu, A Demontis, B Biggio, M Gori, F Roli IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9944
, 2021 | 32* | 2021 |
| Fader: Fast adversarial example rejection F Crecchi, M Melis, A Sotgiu, D Bacciu, B Biggio Neurocomputing 470, 257-268, 2022 | 23 | 2022 |
| Intelliav: Toward the feasibility of building intelligent anti-malware on android devices M Ahmadi, A Sotgiu, G Giacinto Machine Learning and Knowledge Extraction: First IFIP TC 5, WG 8.4, 8.9, 12
, 2017 | 20 | 2017 |
| Explainability-based debugging of machine learning for vulnerability discovery A Sotgiu, M Pintor, B Biggio Proceedings of the 17th International Conference on Availability
, 2022 | 15 | 2022 |
| Intelliav: Building an effective on-device android malware detector M Ahmadi, A Sotgiu, G Giacinto arXiv preprint arXiv:1802.01185, 2018 | 12 | 2018 |
| Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving M Pintor, L Demetrio, A Sotgiu, HY Lin, C Fang, A Demontis, B Biggio 2023 International Conference on Machine Learning and Cybernetics (ICMLC), 57-62, 2023 | | 2023 |
| Evaluating Adversarial Robustness of Detection-based Defenses against Adversarial Examples A Sotgiu Università degli Studi di Cagliari, 2023 | | 2023 |
| AI Security and Safety: The PRALab Research Experience A Demontis, M Pintor, L Demetrio, A Sotgiu, D Angioni, G Piras, S Gupta, ... CEUR WORKSHOP PROCEEDINGS 3486, 324-328, 2023 | | 2023 |
