Privacy-Preserving Authentication in Mobile Edge Computing

Abstract

Mobile Edge Computing (MEC) brings computation and storage closer to users, enabling low-latency services for IoT, 5G, and real-time applications. However, the distributed and decentralized nature of MEC introduces complex security and privacy challenges, particularly in authentication. Traditional cloud-centric authentication schemes fail to meet MEC's demands for lightweight, privacy-preserving, and cross-domain mutual authentication. This paper proposes an integrated privacy-preserving authentication framework tailored for MEC. First, we examine lightweight authentication schemes developed for MEC, including reinforcement-learning-based defense against jamming and collaborative caching with light-weight authentication primitives arXiv. Second, we survey multi-domain authentication challenges in edge environments, emphasizing single-domain and cross-domain authentication needs Building on these insights, we design a protocol that enables end users, edge servers, and infrastructure providers to authenticate each other using elliptic-curve cryptography and attribute-based credentials, ensuring anonymity, untraceability, and low computational cost. The framework supports handover authentication as mobile users roam between edge nodes, preserving privacy across trust domains. Simulation results demonstrate the scheme’s efficiency and resilience compared to baseline methods. This study contributes an academically grounded, practical authentication model addressing MEC's unique demands in 2018 contexts, and offers directions for future development in secure edge ecosystems.