| Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries L Demetrio, B Biggio, G Lagorio, F Roli, A Armando Proceedings of the Third Italian Conference on Cyber Security 2315, 2019 | 182 | 2019 |
| Functionality-preserving Black-box Optimization of Adversarial Windows Malware L Demetrio, B Biggio, G Lagorio, F Roli, A Armando IEEE Transactions on Information Forensics and Security, 2020 | 178 | 2020 |
| Adversarial EXEmples: a survey and experimental evaluation of practical attacks on machine learning for windows malware detection L Demetrio, SE Coull, B Biggio, G Lagorio, A Armando, F Roli ACM Transactions on Privacy and Security (TOPS) 24 (4), 1-31, 2021 | 161 | 2021 |
| 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 | 59 | 2023 |
| WAF-A-MoLE: Evading Web Application Firewalls through Adversarial Machine Learning L Demetrio, A Valenza, G Costa, G Lagorio Proceedings of the 35th Annual ACM Symposium on Applied Computing, 1745–1752, 2020 | 44 | 2020 |
| 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 arXiv preprint arXiv:2106.09947, 2021 | 40 | 2021 |
| Phantom sponges: Exploiting non-maximum suppression to attack deep object detectors A Shapira, A Zolfi, L Demetrio, B Biggio, A Shabtai Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 35* | 2023 |
| Towards learning trustworthily, automatically, and with guarantees on graphs: An overview L Oneto, N Navarin, B Biggio, F Errica, A Micheli, F Scarselli, M Bianchini, ... Neurocomputing 493, 217-243, 2022 | 32 | 2022 |
| Secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python L Demetrio, B Biggio arXiv preprint arXiv:2104.12848, 2021 | 24* | 2021 |
| secml: Secure and Explainable Machine Learning in Python M Pintor, L Demetrio, A Sotgiu, M Melis, A Demontis, B Biggio SoftwareX 18, 2022 | 20* | 2022 |
| Practical evaluation of poisoning attacks on online anomaly detectors in industrial control systems M Kravchik, L Demetrio, B Biggio, A Shabtai Computers & Security 122, 102901, 2022 | 16 | 2022 |
| Practical Attacks on Machine Learning: A Case Study on Adversarial Windows Malware L Demetrio, B Biggio, F Roli IEEE Security & Privacy, 2022 | 16 | 2022 |
| ZenHackAdemy: Ethical Hacking@ DIBRIS. L Demetrio, G Lagorio, M Ribaudo, E Russo, A Valenza CSEDU (1), 405-413, 2019 | 13 | 2019 |
| WAF-A-MoLE: An adversarial tool for assessing ML-based WAFs A Valenza, L Demetrio, G Costa, G Lagorio SoftwareX 11, 100367, 2020 | 10 | 2020 |
| Nebula: Self-attention for dynamic malware analysis D Trizna, L Demetrio, B Biggio, F Roli IEEE Transactions on Information Forensics and Security, 2024 | 8 | 2024 |
| Raze to the ground: Query-efficient adversarial html attacks on machine-learning phishing webpage detectors B Montaruli, L Demetrio, M Pintor, L Compagna, D Balzarotti, B Biggio Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security …, 2023 | 8 | 2023 |
| Explaining machine learning DGA detectors from DNS traffic data G Piras, M Pintor, L Demetrio, B Biggio arXiv preprint arXiv:2208.05285, 2022 | 7 | 2022 |
| Explaining vulnerabilities of deep learning to adversarial malware binaries. arXiv 2019 L Demetrio, B Biggio, G Lagorio, F Roli, A Armando arXiv preprint arXiv:1901.03583, 0 | 6 | |
| Attackbench: Evaluating gradient-based attacks for adversarial examples AE Cinà, J Rony, M Pintor, L Demetrio, A Demontis, B Biggio, IB Ayed, ... arXiv preprint arXiv:2404.19460, 2024 | 4 | 2024 |
| Robustness-congruent adversarial training for secure machine learning model updates D Angioni, L Demetrio, M Pintor, L Oneto, D Anguita, B Biggio, F Roli arXiv preprint arXiv:2402.17390, 2024 | 4 | 2024 |
Battista BiggioFull Professor, University of Cagliari, ItalyPreverjeni e-poštni naslov na unica.it