| The malicious use of artificial intelligence: Forecasting, prevention, and mitigation M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ... arXiv preprint arXiv:1802.07228, 2018 | 1257 | 2018 |
| Ember: an open dataset for training static pe malware machine learning models HS Anderson, P Roth arXiv preprint arXiv:1804.04637, 2018 | 614 | 2018 |
| Predicting domain generation algorithms with long short-term memory networks J Woodbridge, HS Anderson, A Ahuja, D Grant arXiv preprint arXiv:1611.00791, 2016 | 308 | 2016 |
| DeepDGA: Adversarially-tuned domain generation and detection HS Anderson, J Woodbridge, B Filar Proceedings of the 2016 ACM workshop on artificial intelligence and security …, 2016 | 271 | 2016 |
| Learning to evade static PE machine learning malware models via reinforcement learning HS Anderson, A Kharkar, B Filar, D Evans, P Roth arXiv preprint arXiv:1801.08917, 2018 | 259 | 2018 |
| Evading machine learning malware detection HS Anderson, A Kharkar, B Filar, P Roth black Hat 2017, 1-6, 2017 | 252 | 2017 |
| Poisoning web-scale training datasets is practical N Carlini, M Jagielski, CA Choquette-Choo, D Paleka, W Pearce, ... 2024 IEEE Symposium on Security and Privacy (SP), 407-425, 2024 | 196 | 2024 |
| Tree of attacks: Jailbreaking black-box llms automatically A Mehrotra, M Zampetakis, P Kassianik, B Nelson, H Anderson, Y Singer, ... Advances in Neural Information Processing Systems 37, 61065-61105, 2025 | 188 | 2025 |
| “real attackers don't compute gradients”: bridging the gap between adversarial ml research and practice G Apruzzese, HS Anderson, S Dambra, D Freeman, F Pierazzi, K Roundy 2023 IEEE conference on secure and trustworthy machine learning (SaTML), 339-364, 2023 | 110 | 2023 |
| The Malicious Use of Artificial Intelligence: Forecasting M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ... Prevention, and Mitigation 20, 2018 | 99 | 2018 |
| Sparse imaging for fast electron microscopy HS Anderson, J Ilic-Helms, B Rohrer, J Wheeler, K Larson Computational Imaging XI 8657, 94-105, 2013 | 83 | 2013 |
| Classifying with confidence from incomplete information N Parrish, HS Anderson, MR Gupta, DY Hsiao The Journal of Machine Learning Research 14 (1), 3561-3589, 2013 | 72 | 2013 |
| Real-time 3D ladar imaging P Cho, H Anderson, R Hatch, P Ramaswami 35th IEEE Applied Imagery and Pattern Recognition Workshop (AIPR'06), 5-5, 2006 | 69 | 2006 |
| Classifying sequences of extreme length with constant memory applied to malware detection E Raff, W Fleshman, R Zak, HS Anderson, B Filar, M McLean Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9386-9394, 2021 | 68 | 2021 |
| Sea ice mapping method for SeaWinds HS Anderson, DG Long IEEE Transactions on Geoscience and Remote Sensing 43 (3), 647-657, 2005 | 67 | 2005 |
| Adversarial machine learning: A taxonomy and terminology of attacks and mitigations A Vassilev, A Oprea, A Fordyce, H Andersen Apostol Vassilev, Alina Oprea, Alie Fordyce, Hyrum Andersen, 2024 | 63 | 2024 |
| The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv 2018 M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ... arXiv preprint arXiv:1802.07228, 2020 | 51 | 2020 |
| Automatic yara rule generation using biclustering E Raff, R Zak, G Lopez Munoz, W Fleming, HS Anderson, B Filar, ... Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security …, 2020 | 47 | 2020 |
| Detecting homoglyph attacks with a siamese neural network J Woodbridge, HS Anderson, A Ahuja, D Grant 2018 IEEE Security and Privacy Workshops (SPW), 22-28, 2018 | 42 | 2018 |
| Adversarial machine learning A Vassilev, A Oprea, A Fordyce, H Anderson Gaithersburg, MD, 2024 | 29 | 2024 |
Bobby FilarSublime SecurityCorreu electrònic verificat a sublimesecurity.com