Deception in Security -- The Risk of Attacker Behavioral Learning: Can Attacker Fool Defender under Uncertainty? .-Casino Rationale: Countering attacker deception in zero-sum Stackelberg security games of bounded rationality -- Cyber Deception against Zero-day Attacks: A Game Theoretic Approach -- Planning and Learning in Dynamic Enviroments -- On Almost-Sure Intention Deception Planning that Exploits Imperfect Observers -- Using Deception in Markov Game to Understand Adversarial Behaviors through a Capture-The-Flag Environment -- Robust Moving Target Defense against Unknown Attacks: A Meta-Reinforcement Learning Approach -- Security Games -- Synchronization in Security Games -- Multiple Oracle Algorithm to Solve Continuous Games -- Optimal Pursuit of Surveilling Agents near a High Value Target -- Adversarial Learning and Optimization -- On Poisoned Wardrop Equilibrium in Congestion Games -- Reward Delay Attacks on Deep Reinforcement Learning -- An Exploration of Poisoning Attacks on Data-based Decision Making -- Novel Applications and new Game Models -- A Network Centrality Game for Epidemic Control -- Optimizing Intrusion Detection Systems Placement against Network Virus Spreading using a Partially Observable Stochastic Minimum-Threat Path Game -- Voting Games to Model Protocol Stability and Security of Proof-of-Work Cryptocurrencies.

This book constitutes the refereed proceedings of the 13th International Conference on Decision and Game Theory for Security, GameSec 2022, held in October 2022 in Pittsburgh, PA, USA. The 15 full papers presented were carefully reviewed and selected from 39 submissions. The papers are grouped thematically on: deception in security; planning and learning in dynamic environments; security games; adversarial learning and optimization; novel applications and new game models.