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
Position: “Real Attackers Don’t Compute Gradients”: Bridging the Gap Between Adversarial ML Research and Practice Apruzzese, G., Anderson, H., Dambra, S., Freeman, D., Pierazzi, F. & Roundy, K., 15 Nov 2022, (Accepted/In press) IEEE Conference on Secure and Trustworthy Machine Learning. IEEE Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review Exploring the Security and Privacy Risks of Chatbots in Messaging Services Edu, J., Mulligan, C., Pierazzi, F., Polakis, J., Suarez-Tangil, G. & Such, J., 19 Sep 2022, (Accepted/In press) Proceedings of the 22nd ACM Internet Measurement Conference (IMC '22), October 25--27, 2022, Nice, France: ACM. Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review 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 View all publications