| 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 | 627 | 2022 |
| 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 | 587 | 2019 |
| 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 | 424 | 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 | 182 | 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 | 170* | 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 | 54 | 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 | 50 | 2021 |
| Realizable universal adversarial perturbations for malware R Labaca-Castro, L Muñoz-González, F Pendlebury, GD Rodosek, ... arXiv preprint arXiv:2102.06747, 2021 | 35* | 2021 |
| 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 | 19 | 2023 |
| 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 | 18 | 2023 |
| 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 | 18* | 2018 |
| 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 | 12 | 2024 |
| 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 | 8 | 2023 |
| 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 | 6 | 2024 |
| Machine learning for security in hostile environments F Pendlebury University of London, 2021 | 4 | 2021 |
| Intriguing Properties of Adversarial ML Attacks in the Problem Space [Extended Version] J Cortellazzi, E Quiring, D Arp, F Pendlebury, F Pierazzi, L Cavallaro ACM Transactions on Privacy and Security, 2025 | 3 | 2025 |
| 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, ... | | |
Fabio PierazziAssociate Professor at University College LondonVerified email at ucl.ac.uk
