Dr Fabio Pierazzi Dr Fabio Pierazzi Academics Supervisors Lecturer in Computer Science Research subject areas Computer science Contact details +44 020 7848 2390 fabio.pierazzi@kcl.ac.uk
WoRMA '22: 1st Workshop on Robust Malware Analysis Pierazzi, F. & Srndic, N., 30 May 2022, ASIA CCS 2022 - Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery, Inc, p. 1271-1272 2 p. (ASIA CCS 2022 - Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review. DOIs: https://doi.org/10.1145/3488932.3517205 Transcending TRANSCEND: Revisiting Malware Classification in the Presence of Concept Drift Barbero, F., Pendlebury, F., Pierazzi, F. & Cavallaro, L., May 2022, IEEE Symposium on Security and Privacy (S&P). 43rd ed. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review Investigating Labelless Drift Adaptation for Malware Detection Kan, Z., Pendlebury, F., Pierazzi, F. & Cavallaro, L., 15 Sep 2021, (Accepted/In press) Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security (AISec). ACM Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection Andresini, G., Pendlebury, F., Pierazzi, F., Loglisci, C., Appice, A. & Cavallaro, L., 8 Sep 2021, (Accepted/In press) Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security (AISec). ACM Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review Dos and Don'ts of Machine Learning in Computer Security Daniel Arp, Erwin Quiring, Feargus Pendlebury, Alexander Warnecke, Christian Wressnegger & Konrad Rieck, 15 Jul 2021, (Accepted/In press) Dos and Don'ts of Machine Learning in Computer Security. 2022 ed. USENIX, (Usenix Security Symposium (USENIX)). Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review GLYPH: Efficient ML-based Detection of Heap Spraying Attacks Pierazzi, F., Cristalli, S., Bruschi, D., Colajanni, M., Marchetti, M. & Lanzi, A., 5 Aug 2020, (Accepted/In press) In: IEEE Transactions on Information Forensics and Security. Research output: Contribution to journal › Article › peer-review A Data-Driven Characterization of Modern Android Spyware Pierazzi, F., Mezzour, G., Han, Q., Colajanni, M. & Subrahmanian, V. S., 5 Feb 2020, (Accepted/In press) In: ACM TRANSACTIONS ON INFORMATION SYSTEMS. Research output: Contribution to journal › Article › peer-review Intriguing Properties of Adversarial ML Attacks in the Problem Space Pierazzi, F., Pendlebury, F., Cortellazzi, J. & Cavallaro, L., 18 May 2020, In: 2020 IEEE Symposium on Security and Privacy. p. 1332-1349 18 p. Research output: Contribution to journal › Conference paper › peer-review. DOIs: https://doi.org/10.1109/SP40000.2020.00073 Analysis of high volumes of network traffic for Advanced Persistent Threat detection Marchetti, M., Pierazzi, F., Colajanni, M. & Guido, A., 9 Nov 2016, In: COMPUTER NETWORKS. 109, p. 127-141 15 p. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1016/j.comnet.2016.05.018 A Probabilistic Logic of Cyber Deception Jajodia, S., Park, N., Pierazzi, F., Pugliese, A., Serra, E., Simari, G. & Subrahmanian, V. S., 1 Nov 2017, In: IEEE Transactions on Information Forensics and Security. 12, 11, p. 2532-2544 13 p., 7937934. Research output: Contribution to journal › Article › peer-review. DOIs: https://doi.org/10.1109/TIFS.2017.2710945 View all publications