TESSERACT: Eliminating experimental bias in malware classification across space and time F Pendlebury, F Pierazzi, R Jordaney, J Kinder, L Cavallaro 28th USENIX Security Symposium (USENIX Security 19), 729-746, 2019 | 397 | 2019 |
Dos and don’ts of machine learning in computer security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... 31st USENIX Security Symposium (USENIX Security '22), 2022 | 337 | 2022 |
Intriguing Properties of Adversarial ML Attacks in the Problem Space F Pierazzi, F Pendlebury, J Cortellazzi, L Cavallaro 2020 IEEE Symposium on Security and Privacy (SP), 1332-1349, 2020 | 289 | 2020 |
Insomnia: Towards concept-drift robustness in network intrusion detection G Andresini, F Pendlebury, F Pierazzi, C Loglisci, A Appice, L Cavallaro Proceedings of the 14th ACM workshop on artificial intelligence and security …, 2021 | 78 | 2021 |
Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift F Barbero, F Pendlebury, F Pierazzi, L Cavallaro 2022 IEEE Symposium on Security and Privacy (SP), 2022 | 69* | 2022 |
Realizable universal adversarial perturbations for malware R Labaca-Castro, L Muñoz-González, F Pendlebury, GD Rodosek, ... arXiv preprint arXiv:2102.06747, 2021 | 24* | 2021 |
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers L Yang, Z Chen, J Cortellazzi, F Pendlebury, K Tu, F Pierazzi, L Cavallaro, ... 2023 IEEE Symposium on Security and Privacy (SP), 2023 | 21 | 2023 |
Investigating labelless drift adaptation for malware detection Z Kan, F Pendlebury, F Pierazzi, L Cavallaro Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security …, 2021 | 20 | 2021 |
Enabling Fair ML Evaluations for Security F Pendlebury, F Pierazzi, R Jordaney, J Kinder, L Cavallaro Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018 | 15* | 2018 |
Are machine learning models for malware detection ready for prime time? L Cavallaro, J Kinder, F Pendlebury, F Pierazzi IEEE Security & Privacy 21 (2), 53-56, 2023 | 10 | 2023 |
Is it overkill? analyzing feature-space concept drift in malware detectors Z Chen, Z Zhang, Z Kan, L Yang, J Cortellazzi, F Pendlebury, F Pierazzi, ... 2023 IEEE Security and Privacy Workshops (SPW), 21-28, 2023 | 5 | 2023 |
Machine learning for security in hostile environments F Pendlebury University of London, 2021 | 2 | 2021 |
Lessons Learned on Machine Learning for Computer Security D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ... IEEE Security & Privacy 21 (5), 72-77, 2023 | 1 | 2023 |
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version) Z Kan, S McFadden, D Arp, F Pendlebury, R Jordaney, J Kinder, ... arXiv preprint arXiv:2402.01359, 2024 | | 2024 |
Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version] J Cortellazzi, F Pendlebury, D Arp, E Quiring, F Pierazzi, L Cavallaro arXiv e-prints, arXiv: 1911.02142, 2019 | | 2019 |