Conference Information
GameSec 2026: Conference on Game Theory and AI for Security
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Submission Date:
2026-06-12
Notification Date:
2026-07-31
Conference Date:
2026-10-26
Location:
Ann Arbor, Michigan, USA
Years:
17
Viewed: 26781   Tracked: 4   Attend: 2

Call For Papers
Conference Topics

Indicative topics, but not exhaustive, are listed below, and the conference welcomes a broad range of contributions exploring the intersection of game theory, AI, and security.

Stackelberg and Bayesian games for cybersecurity
Mechanism design for secure and resilient systems
Multi-agent security games and adversarial interactions
Dynamic and repeated games in security applications
Coalitional game theory for trust and privacy
Evolutionary game theory in cyber defense
Game-theoretic models for deception and misinformation detection
Auction-based security mechanisms for resource allocation
Nash equilibria in adversarial security settings
Aggregative Games for security

Adversarial machine learning and robust AI models
Reinforcement learning for cyber defense strategies
AI-driven risk assessment and threat intelligence
Secure federated learning and privacy-preserving AI
AI for zero-trust architectures and intrusion detection
Explainable AI in security decision-making
Large language models for cybersecurity applications
AI-powered malware and phishing detection
Automated penetration testing and ethical hacking using AI

Game-theoretic approaches for securing IoT and edge computing
Security strategies for autonomous systems and UAVs
AI-driven attack detection in smart grids and critical infrastructures
Secure network protocols and AI-powered anomaly detection
Blockchain and game theory for decentralized security
Cyber-physical system resilience through game-theoretic modeling
Security strategies for smart cities and intelligent transportation systems
AI-enhanced situational awareness in cyber-physical environments

Incentive mechanisms for cybersecurity investments
Human-in-the-loop security and behavioral game theory
Trust and reputation models in decentralized systems
AI-powered fraud detection in financial systems
Privacy-aware mechanism design and data-sharing incentives
Economic impact of cyber threats and attack mitigation strategies
Psychological and cognitive biases in security decision-making

Red teaming and AI-generated attack simulations
Robust AI models against adversarial perturbations
AI-powered misinformation and propaganda detection
Security challenges in generative AI and large language models
Ethical AI and fairness in security decision-making
AI for detecting and mitigating deepfake threats
Secure AI model training and adversarial robustness testing
Reinforcement learning under adversarial conditions

Game-theoretic approaches to securing blockchain networks
AI for decentralized identity and authentication management
Security challenges in multi-agent and swarm intelligence systems
Incentive-driven security solutions for distributed systems
AI-powered smart contract verification and fraud detection
Secure consensus mechanisms in blockchain and distributed ledgers

AI-driven security in autonomous transportation
Game theory for cloud security and access control
AI-enhanced cyber resilience in government and military networks
AI for misinformation mitigation in social networks
AI and game theory applications in healthcare cybersecurity
Security in quantum computing and post-quantum cryptography
AI-powered cybersecurity solutions for industrial control systems
AI in securing 5G/6G and next-generation communication networks
Last updated by Dou Sun in 2026-03-11
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