@conference {1499553,
	title = {General-Sum Cyber Deception Games under Partial Attacker Valuation Information},
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (Extended Abstract) (AAMAS-19)},
	year = {2019},
	abstract = {The rapid increase in cybercrime, causing a reported annual economic loss of $600 billion [20], has prompted a critical need foreffective cyber defense. Strategic criminals conduct network reconnaissance prior to executing attacks to avoid detection and establishsituational awareness via scanning and fingerprinting tools. Cyberdeception 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 deceptionmethods. Recently introduced initial model for CDGs assumes zerosum payoffs, implying directly conflicting attacker motives, andperfect defender knowledge on attacker preferences. These unrealistic assumptions are fundamental limitations of the initial zero-summodel, which we address by proposing a general-sum model thatcan also handle uncertainty in the defender{\textquoteright}s knowledge.},
	author = {Thakoor, Omkar and Tambe, Milind and Vayanos, Phebe and Haifeng Xu and Kiekintveld, Christopher}
}
