Foundations of Cyber Resilience: The Confluence of Game, Control, and Learning Theories
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Abstract (arXiv)
Cyber resilience is a complementary concept to cybersecurity, focusing on the preparation, response, and recovery from cyber threats that are challenging to prevent. Organizations increasingly face such threats in an evolving cyber threat landscape. Understanding and establishing foundations for cyber resilience provide a quantitative and systematic approach to cyber risk assessment, mitigation policy evaluation, and risk-informed defense design. A systems-scientific view toward cyber risks provides holistic and system-level solutions. This chapter starts with a systemic view toward cyber risks and presents the confluence of game theory, control theory, and learning theories, which are three major pillars for the design of cyber resilience mechanisms to counteract increasingly sophisticated and evolving threats in our networks and organizations. Game and control theoretic methods provide a set of modeling frameworks to capture the strategic and dynamic interactions between defenders and attackers. Control and learning frameworks together provide a feedback-driven mechanism that enables autonomous and adaptive responses to threats. Game and learning frameworks offer a data-driven approach to proactively reason about adversarial behaviors and resilient strategies. The confluence of the three lays the theoretical foundations for the analysis and design of cyber resilience. This chapter presents various theoretical paradigms, including dynamic asymmetric games, moving horizon control, conjectural learning, and meta-learning, as recent advances at the intersection. This chapter concludes with future directions and discussions of the role of neurosymbolic learning and the synergy between foundation models and game models in cyber resilience.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Apr 2024.
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Citing papers per year: 2024: 1; 2025: 3; 2026: 5.
9 papers.
- 2025Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threatscited by 10
- 2025Agentic AI for Cyber Resilience: A New Security Paradigm and Its System-Theoretic Foundationscited by 4
- 2026Insurance of Agentic AIcited by 2
- 2025Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learningcited by 1
- 2024The Game-Theoretic Symbiosis of Trust and AI in Networked Systemscited by 0
- 2026Agentomics: Economic Foundations for the Valuation, Attribution, and Pricing of AI Agents in Human-AI Workflowscited by 0
- 2026A Variational Framework for LLM Generator-Regulator Gamescited by 0
- 2026AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Modelscited by 0
- 2026Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestrationcited by 0
- 2026Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration14 Jul 2026
- 2026A Variational Framework for LLM Generator-Regulator Games16 Jun 2026
- 2026AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models10 Jun 2026
- 2026Agentomics: Economic Foundations for the Valuation, Attribution, and Pricing of AI Agents in Human-AI Workflows9 Jun 2026
- 2026Insurance of Agentic AI3 Jun 2026
- 2025Agentic AI for Cyber Resilience: A New Security Paradigm and Its System-Theoretic Foundations28 Dec 2025
- 2025Game Theory Meets LLM and Agentic AI: Reimagining Cybersecurity for the Age of Intelligent Threats14 Jul 2025
- 2025Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning26 Jan 2025
- 2024The Game-Theoretic Symbiosis of Trust and AI in Networked Systems19 Nov 2024