| Towards poisoning of deep learning algorithms with back-gradient optimization L Muñoz-González, B Biggio, A Demontis, A Paudice, V Wongrassamee, ... Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017 | 497 | 2017 |
| Adversarial malware binaries: Evading deep learning for malware detection in executables B Kolosnjaji, A Demontis, B Biggio, D Maiorca, G Giacinto, C Eckert, ... 2018 26th European signal processing conference (EUSIPCO), 533-537, 2018 | 300 | 2018 |
| Yes, machine learning can be more secure! a case study on android malware detection A Demontis, M Melis, B Biggio, D Maiorca, D Arp, K Rieck, I Corona, ... IEEE Transactions on Dependable and Secure Computing, 2017 | 277 | 2017 |
| Why do adversarial attacks transfer? explaining transferability of evasion and poisoning attacks A Demontis, M Melis, M Pintor, M Jagielski, B Biggio, A Oprea, ... 28th USENIX security symposium (USENIX security 19), 321-338, 2019 | 261 | 2019 |
| Is deep learning safe for robot vision? adversarial examples against the icub humanoid M Melis, A Demontis, B Biggio, G Brown, G Fumera, F Roli Proceedings of the IEEE international conference on computer vision …, 2017 | 103 | 2017 |
| Secure kernel machines against evasion attacks P Russu, A Demontis, B Biggio, G Fumera, F Roli Proceedings of the 2016 ACM workshop on artificial intelligence and security …, 2016 | 69 | 2016 |
| 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 | 40 | 2020 |
| On security and sparsity of linear classifiers for adversarial settings A Demontis, P Russu, B Biggio, G Fumera, F Roli Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2016 | 40 | 2016 |
| secml: A python library for secure and explainable machine learning M Melis, A Demontis, M Pintor, A Sotgiu, B Biggio arXiv preprint arXiv:1912.10013, 2019 | 28 | 2019 |
| Adversarial detection of flash malware: Limitations and open issues D Maiorca, A Demontis, B Biggio, F Roli, G Giacinto Computers & Security 96, 101901, 2020 | 24 | 2020 |
| Do gradient-based explanations tell anything about adversarial robustness to android malware? M Melis, M Scalas, A Demontis, D Maiorca, B Biggio, G Giacinto, F Roli International journal of machine learning and cybernetics, 1-16, 2022 | 20 | 2022 |
| Can domain knowledge alleviate adversarial attacks in multi-label classifiers? S Melacci, G Ciravegna, A Sotgiu, A Demontis, B Biggio, M Gori, F Roli | 17* | 2020 |
| The threat of offensive ai to organizations Y Mirsky, A Demontis, J Kotak, R Shankar, D Gelei, L Yang, X Zhang, ... Computers & Security, 103006, 2022 | 16 | 2022 |
| Wild patterns reloaded: A survey of machine learning security against training data poisoning AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ... arXiv preprint arXiv:2205.01992, 2022 | 13 | 2022 |
| Infinity-norm support vector machines against adversarial label contamination A Demontis, B Biggio, G Fumera, G Giacinto, F Roli CEUR WORKSHOP PROCEEDINGS 1816, 106-115, 2017 | 13 | 2017 |
| 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 | 12 | 2022 |
| Super-sparse regression for fast age estimation from faces at test time A Demontis, B Biggio, G Fumera, F Roli Image Analysis and Processing—ICIAP 2015: 18th International Conference …, 2015 | 9 | 2015 |
| Why adversarial reprogramming works, when it fails, and how to tell the difference Y Zheng, X Feng, Z Xia, X Jiang, A Demontis, M Pintor, B Biggio, F Roli Information Sciences, 2023 | 8 | 2023 |
| Super-sparse learning in similarity spaces A Demontis, M Melis, B Biggio, G Fumera, F Roli IEEE Computational Intelligence Magazine 11 (4), 36-45, 2016 | 7 | 2016 |
| 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 | 6 | 2023 |
Battista BiggioAssociate Professor at University of Cagliari, Co-Founder of Pluribus OneEmail verificata su unica.it
