Fabio Pierazzi
Senior Lecturer (Associate Professor) in Computer Science at King's College London
Deputy Head of the Cybersecurity Group in Informatics
Programme Leader of the MSc in Cyber Security
Office BH(N)7.16
Dept. Informatics
King's College London
I am invested into understanding how AI can be used to improve systems security tasks, with a particular emphasis on settings in which attackers adapt quickly to new defenses. In this context, I am currently exploring how to measure, mitigate and prevent concept drift in ML-based detection systems; how to measure and improve robustness of systems to adversarial attacks while taking into account problem-space constraints (such as preserving semantics of modified code); and how to explain what these systems are doing, both from an attacker’s and a defender’s perspective.
I also care deeply about the practicality of our proposed solutions, and on understanding implications and limitations of using AI in the context of computer security. To this purpose, I also regularly engage and collaborate with industry. I mostly work on malware analysis and network traffic, but I am becoming more interested in understanding inner workings of AI and ML models to improve their trustworthiness in more general security scenarios.
I am always looking for motivated students and collaborators passionate about these topics. If you are interested in joining my team, or even just visiting, have a look here.
news
Sep 20, 2024 | Jacopo successfully passed his Ph.D. viva, with the usual minor amendments! |
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Sep 15, 2024 | New papers accepted at two CCS Workshops: AISec24 and CPSIoTSec24. |
Sep 6, 2024 | Marcus successfully passed his Ph.D. viva, with the usual minor amendments! |
Jul 17, 2024 | New paper led by Jacopo and Ilias accepted at RAID 2024. |
Jul 15, 2024 | I am in the Program Committees of IEEE EuroS&P, SaTML and USENIX Security 2025. |
latest posts
Mar 22, 2022 | Malware Datasets with Timestamps |
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Oct 29, 2021 | How to Review Literature in Systems Security |
Mar 2, 2019 | Introduction to Python multiprocessing |
selected publications
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