Static malware detection & subterfuge: Quantifying the robustness of machine learning and current anti-virus W Fleshman, E Raff, R Zak, M McLean, C Nicholas 2018 13th International Conference on Malicious and Unwanted Software …, 2018 | 53 | 2018 |
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 | 49 | 2021 |
Non-negative networks against adversarial attacks W Fleshman, E Raff, J Sylvester, S Forsyth, M McLean arXiv preprint arXiv:1806.06108, 2018 | 33 | 2018 |
Spectral Clustering, Foundation and Application W Fleshman consulted in June/2022, https://towardsdatascience. com/spectral-clustering …, 2019 | 5 | 2019 |
Evading machine learning malware classifiers W Fleshman | 5 | 2019 |
Static malware detection & subterfuge: Quantifying the robustness of machine learning and current anti-virus. arXiv 2018 W Fleshman, E Raff, R Zak, M McLean, C Nicholas arXiv preprint arXiv:1806.04773, 0 | 3 | |
Evading Machine Learning Malware Classifiers, 2019 W Fleshman URL https://towardsdatascience. com/evading-machine-learning …, 0 | 2 | |
Deception and the Strategy of Influence B Brian, W Fleshman, H Kevin, R Kaliszewski arXiv e-prints, arXiv: 2011.01331, 2020 | 1 | 2020 |
AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees W Fleshman, A Khan, M Marone, B Van Durme arXiv preprint arXiv:2404.08417, 2024 | | 2024 |
Toucan: Token-Aware Character Level Language Modeling W Fleshman, B Van Durme arXiv preprint arXiv:2311.08620, 2023 | | 2023 |
Deception and the Strategy of Influence W Fleshman, R Kaliszewski arXiv preprint arXiv:2011.01331, 2020 | | 2020 |