154 citations · 639 across the 138 of their papers we have counts for
3 papers · 2 filters
Adversarial Deep Reinforcement Learning based Adaptive Moving Target Defense
Taha Eghtesad, Yevgeniy Vorobeychik, Aron Laszka
Moving target defense (MTD) is a proactive defense approach that aims to thwart attacks by continuously changing the attack surface of a system (e.g., changing host or network conf…
Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning
Liang Tong, Aron Laszka, Chao Yan +2
Detection of malicious behavior is a fundamental problem in security. One of the major challenges in using detection systems in practice is in dealing with an overwhelming number o…
To Warn or Not to Warn: Online Signaling in Audit Games
Chao Yan, Haifeng Xu, Yevgeniy Vorobeychik +3
Routine operational use of sensitive data is often governed by law and regulation. For instance, in the medical domain, there are various statues at the state and federal level tha…