Enabling Technologies for Next Generation of Mobile Networks: A Survey of Security, Trust and Privacy Threats & Protection Opportunities

Abstract

As the limitations of the current cellular network generation have become apparent to tackle current connectivity needs in 6G, the scientific communities have started to investigate novel techniques to bolster the capabilities of the communication infrastructure. Within 6G, Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) are envisioned as key enablers to drive network performance and guarantee process integrity. However, from a security standpoint, those methods are dual-edged as they introduce a new threat surface that could be used to jeopardise the platform security, the trust in service utility and data privacy. This survey provides a consolidated review of the security, trust, and privacy impact of key 6G enabling technologies. The analysis begins by identifying the primary architectural drivers anticipated for next-generation mobile networks, systematically mapping their impact on the threat surface to identify critical resilience challenges. Conversely, we pinpoint protection methodologies enacted by these drivers, outlining concrete countermeasures that enhance the network’s security posture. Finally, we propose a unified reference architecture that integrates these benefits for holistic security, privacy, and trust management, complemented by a system-level evaluation.