Toward Autonomous 6G Networks: A Trust-Centric and Privacy-Preserving Framework
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ABSTRACT: The move towards sixth-generation networks poses unprecedented challenges in terms of security, trust, and privacy due to the integration of artificial intelligence, Internet of Things, and global communication networks. In this context, this paper aims to provide an exhaustive systematic literature review of existing 6G research with existing trust models proposed by the International Telecommunication Union (ITU-T) and analyze the interrelated relationship between privacy preservation, energy efficiency, and autonomous systems. This research is based on an exhaustive analysis of existing peer-reviewed articles from 2020 to 2026, white papers, and existing frameworks. It is evident from this analysis that existing research is largely focused on the individual optimization of privacy preservation, energy efficiency, and autonomous systems, leading to an inherent trade-off. This paper aims to provide an exhaustive framework for integrating privacy preservation, energy efficiency, and autonomous systems as pillars of 6G networks. Key findings include that Edge Intelligence, Federated Learning, Zero Trust Architecture, and Post-Quantum Cryptography act as key enablers in meeting these often conflicting requirements. The study concludes by identifying 12 distinct research gaps and suggesting future directions toward cooperative, AI-driven, and quantum-resistant trust architectures for 6G. This study contributes to the SAMRNET (Security, Architecture, Management, and Resilience of NETworks) research agenda by establishing a comprehensive foundation for trust-centric 6G network design.
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