# The Game-Theoretic Symbiosis of Trust and AI in Networked Systems

arXiv: https://arxiv.org/abs/2411.12859 · HTML: https://mlsanity.com/paper/2411.12859/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 66 references that are in the map.
- First posted on arXiv 19 Nov 2024.

## Builds on (most cited first, 13 of 13)

- [PenHeal: A Two-Stage LLM Framework for Automated Pentesting and Optimal Remediation](https://mlsanity.com/paper/2407.17788/) (2024)
- [Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Games](https://mlsanity.com/paper/2402.18781/) (2024)
- [Scenario-Agnostic Zero-Trust Defense with Explainable Threshold Policy: A Meta-Learning Approach](https://mlsanity.com/paper/2303.03349/) (2023)
- [Foundations of Cyber Resilience: The Confluence of Game, Control, and Learning Theories](https://mlsanity.com/paper/2404.01205/) (2024)
- [Meta Stackelberg Game: Robust Federated Learning against Adaptive and Mixed Poisoning Attacks](https://mlsanity.com/paper/2410.17431/) (2024)
- [Symbiotic Game and Foundation Models for Cyber Deception Operations in Strategic Cyber Warfare](https://mlsanity.com/paper/2403.10570/) (2024)
- [Deception by Design: Evidence-Based Signaling Games for Network Defense](https://mlsanity.com/paper/1503.05458/) (2015)
- [Informational Design of Dynamic Multi-Agent System](https://mlsanity.com/paper/2105.03052/) (2021)
- [Accountability and Insurance in IoT Supply Chain](https://mlsanity.com/paper/2201.11855/) (2022)
- [Zero Trust for Cyber Resilience](https://mlsanity.com/paper/2312.02882/) (2023)
- [Attributing Responsibility in AI-Induced Incidents: A Computational Reflective Equilibrium Framework for Accountability](https://mlsanity.com/paper/2404.16957/) (2024)
- [Commitment with Signaling under Double-sided Information Asymmetry](https://mlsanity.com/paper/2212.11446/) (2022)
- [AI Liability Insurance With an Example in AI-Powered E-diagnosis System](https://mlsanity.com/paper/2306.01149/) (2023)

## Abstract (arXiv)

This chapter explores the symbiotic relationship between Artificial Intelligence (AI) and trust in networked systems, focusing on how these two elements reinforce each other in strategic cybersecurity contexts. AI's capabilities in data processing, learning, and real-time response offer unprecedented support for managing trust in dynamic, complex networks. However, the successful integration of AI also hinges on the trustworthiness of AI systems themselves. Using a game-theoretic framework, this chapter presents approaches to trust evaluation, the strategic role of AI in cybersecurity, and governance frameworks that ensure responsible AI deployment. We investigate how trust, when dynamically managed through AI, can form a resilient security ecosystem. By examining trust as both an AI output and an AI requirement, this chapter sets the foundation for a positive feedback loop where AI enhances network security and the trust placed in AI systems fosters their adoption.