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

Yunfei Ge, Quanyan Zhu

TL;DR

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, and investigates how trust, when dynamically managed through AI, can form a resilient security ecosystem.

Abstract

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.

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

TL;DR

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, and investigates how trust, when dynamically managed through AI, can form a resilient security ecosystem.

Abstract

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.

Paper Structure

This paper contains 28 sections, 7 equations, 2 figures, 1 table.

Figures (2)

  • Figure 1: Trust is integral to all stages of a networked system. A trustworthy network system ensures reliability from preparation and operation through to the outcomes.
  • Figure 2: The symbiotic relationship between AI and Trust forms a cyber trust ecosystem, with each reinforcing the other.

Theorems & Definitions (2)

  • definition 1: Trust Score
  • definition 2: Bayesian Trust Update