Trustworthy Security Architectures for AI-Driven Metaverse Experiences
Abstract
AI-driven metaverse platforms are evolving into core infrastructure for work, learning, commerce, and services, but their blend of identity data, behavioral telemetry, sensing, virtual assets, and automated decisions creates complex security and privacy risks. This chapter proposes a trustworthy architecture using zero-trust, privacy-preserving analytics, confidential computing, explainable AI, and continuous risk monitoring to secure scalable, interoperable immersive systems across sectors now.
Fields of Study & Subjects
Access Control and Trust
Explainable Artificial Intelligence (XAI)
Security and Verification in Computing
Publication details
- Journal / source
- Advances in computational intelligence and robotics book series
- Publisher
- IGI Global Scientific Publishing
- Pages
- 217–248
- Publication date
- 30 April 2026
- Document type
- Book chapter