47 citations · 110 across the 28 of their papers we have counts for
12 papers · 1 filter
Proving the Utility of Large Language Models in Cybersecurity Simulations: A Comprehensive Examination
Stylianos Kampakis, Fabio Rovai, Marcos Charalambides +2
Cyber threats continue to escalate in both frequency and sophistication, necessitating more adaptive and scalable defense strategies. This paper explores how Large Language Models…
Measuring Security Without Fooling Ourselves: Why Benchmarking Agents Is Hard
Sahar Abdelnabi, Chris Hicks, Konrad Rieck +1
The benchmarks used to evaluate AI agents in security-critical roles suffer from crucial weaknesses. Building on recent empirical evidence, we characterize three core challenges th…
Building Better Environments for Autonomous Cyber Defence
Chris Hicks, Elizabeth Bates, Shae McFadden +12
In November 2025, the authors ran a workshop on the topic of what makes a good reinforcement learning (RL) environment for autonomous cyber defence (ACD). This paper details the kn…
On The Effectiveness of the UK NIS Regulations as a Mandatory Cybersecurity Reporting Regime
Junade Ali, Chris Hicks
Existing cybersecurity literature lacks a source of empirical, representative data as to the true nature of cyberattacks on Critical National Infrastructure. We have obtained UK-wi…
What if we could hot swap our Biometrics?
Jon Crowcroft, Anil Madhavapeddy, Chris Hicks +2
What if you could really revoke your actual biometric identity, and install a new one, by live rewriting your biological self? We propose some novel mechanisms for hot swapping ide…
From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore +4
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simula…