General-Sum Cyber Deception Games under Partial Attacker Valuation Information


Omkar Thakoor, Milind Tambe, Phebe Vayanos, Haifeng Xu, and Christopher Kiekintveld. 2019. “General-Sum Cyber Deception Games under Partial Attacker Valuation Information.” In International Conference on Autonomous Agents and Multiagent Systems (Extended Abstract) (AAMAS-19).


The rapid increase in cybercrime, causing a reported annual economic loss of $600 billion [20], has prompted a critical need for
effective cyber defense. Strategic criminals conduct network reconnaissance prior to executing attacks to avoid detection and establish
situational awareness via scanning and fingerprinting tools. Cyber
deception attempts to foil these reconnaissance efforts; by disguising network and system attributes, among several other techniques.
Cyber Deception Games (CDG) is a game-theoretic model for optimizing strategic deception, and can apply to various deception
methods. Recently introduced initial model for CDGs assumes zerosum payoffs, implying directly conflicting attacker motives, and
perfect defender knowledge on attacker preferences. These unrealistic assumptions are fundamental limitations of the initial zero-sum
model, which we address by proposing a general-sum model that
can also handle uncertainty in the defender’s knowledge.
See also: 2019