2023/06/11 by Shanto Roy, Nazia Sharmin, Roy, Shanto +9
Computer Science · Engineering · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information and Cyber Security #Infrastructure Resilience and Vulnerability Analysis #Network Security and Intrusion Detection
paper · pdf · doi:10.48550/arxiv.2306.06769
openalex publication_date 2023/06/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Adversarial reconnaissance is a crucial step in sophisticated cyber-attacks as it enables threat actors to find the weakest points of otherwise well-defended systems. To thwart reconnaissance, defenders can employ cyber deception techniques, such as deploying honeypots. In recent years, researchers have made great strides in developing game-theoretic models to find optimal deception strategies. However, most of these game-theoretic models build on relatively simple models of adversarial reconnaissance -- even though reconnaissance should be a focus point as the very purpose of deception is to thwart reconnaissance. In this paper, we first discuss effective cyber reconnaissance mitigation techniques including deception strategies and beyond. Then we provide a review of the literature on deception games from the perspective of modeling adversarial reconnaissance, highlighting key aspects of reconnaissance that have not been adequately captured in prior work. We then describe a probability-theory based model of the adversaries' belief formation and illustrate using numerical examples that this model can capture key aspects of adversarial reconnaissance. We believe that our review and belief model can serve as a stepping stone for developing more realistic and practical deception games.