Prati
Feargus Pendlebury
Feargus Pendlebury
Meta | University College London
Potvrđena adresa e-pošte na meta.com
Naslov
Citirano
Citirano
Godina
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
4842019
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
4392022
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
3462020
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
1162021
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
98*2022
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
362023
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
332021
Realizable universal adversarial perturbations for malware
R Labaca-Castro, L Muñoz-González, F Pendlebury, GD Rodosek, ...
arXiv preprint arXiv:2102.06747, 2021
29*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
16*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
142023
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
92023
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
52023
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
42024
Machine learning for security in hostile environments
F Pendlebury
University of London, 2021
42021
Pitfalls in Machine Learning for Computer Security
D Arp, E Quiring, F Pendlebury, A Warnecke, F Pierazzi, C Wressnegger, ...
Communications of the ACM 67 (11), 104-112, 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 preprint arXiv:1911.02142, 2019
2019
Impact of “TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time”
ACA Competition, S McFadden, Z Kan, D Arp, F Pendlebury, R Jordaney, ...
Elisaweta Masserova Elizabeth Margolin Emiliano De Cristofaro Eric Olsson
E Zeng, B Vanleeuwen, B Abdolmaleki, B Eriksson, B Pinkas, B Oh, ...
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