Publications

L. Huang and Q. Zhu, “Deception and Counter-deception Bayesian Game: Adaptive Defense Strategies Against Advanced Persistent Threats for Cyber-physical Systems," Cyber Deception, E. Al-Shaer, K. Hamlen, J. Wei, and C. Wang (Eds.), Springer, 2019. [Link]

T. Zhang, L. Huang, J. Pawlick and Q. Zhu, “Toward a Mechanism Design Theory for Cyber Deception," Modeling and Design of Secure Internet of Things, C. A. Kamhoua, L. Njilla, A. Kott, S. Shetty (Eds.), IEEE Press, 2020.

J. Pawlick, E. Colbert, and Q. Zhu, “A Game-Theoretic Taxonomy and Survey of Defensive Deception for Cybersecurity and Privacy," ACM Computing Surveys, vol. 52, no. 4, Article 82 (August 2019), 28 pages; [DOI]

T. Zhang and Q. Zhu, “Hypothesis Testing Game for Cyber Deception", 9th Conference on Decision and Game Theory for Security (GameSec), Seattle, WA, USA on Oct. 29-31, 2018.

J. Pawlick_ and Q. Zhu, “Modeling and Analysis of Leaky Deception using Signaling Games with Evidence", IEEE Transactions on Information Forensics and Security (TIFS), vol. 14, no. 7, pp. 1871-1886, July 2019; DOI: 10.1109/tifs.2018.2886472

L. Huang, Q. Zhu, “Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes," Conference on Decision and Game Theory for Security (GameSec), Oct. 30 - Nov. 1, 2019, Stockholm, Sweden.

K Horak, Q. Zhu and B. Bosansky, “Manipulating Adversary's Belief: A Dynamic Game Approach to Deception by Design for Proactive Network Security, " 8th Conference on Decision and Game Theory for Security (GameSec), Oct. 23-25, 2017, Vienna, Austria.

Y. Huang and Q. Zhu, “Reinforcement Learning with Maliciously Manipulated Feedback," Game Theory and Machine Learning for Cyber Security, C. A. Kamhoua, C. Kiekintveld, F., Fang and Q. Zhu (Eds.), IEEE Press, 2020.

L. Huang, Q. Zhu, “Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes," Conference on Decision and Game Theory for Security (GameSec), Oct. 30 - Nov. 1, 2019, Stockholm, Sweden.