A data security and privacy scheme for user quality of experience in a Mobile Edge Computing-based network - Foko Sindjoung, Miguel Landry; Velempini, Mthulisi; Djamegni, Clémentin Tayou (Elsevier Inc., 2023)
Cloud computing has widely been used for applications that require huge computational and data storage resources. Unfortunately, with the advent of new technologies such as fifth generation of cellular networks that provide new applications like IoT, cloud computing presents many limits among which the End-To-End (E2E) latency is the main challenge. These applications generally degrade scenarios that require low latency. Mobile Edge Computing (MEC) has been proposed to solve this issue. MEC brings computing and storage resources from cloud data center to edge data center, closer to end-user equipment to reduce the E2E latency for request processing. However, MEC is vulnerable to security, data privacy, and authentication that affect the end-user Quality of Experience (QoE). It is therefore fundamental that these challenges are addressed to avoid poor user experience due to the lack of security or data privacy. In this paper, we propose a hybrid cryptographic system that uses the symmetric and asymmetric cryptographic systems, to improve data security, privacy, and user authentication in a MEC-based network. We show that our proposed scheme is secured by validating it with the Automated Validation of Internet Security Protocol and Application tool. Simulation results show that our solution consumes less computing resources.
Journal article published in the journal of Array 19 (2023) 100304
Keywords: Autonomous vehicular network; Data security and privacy; Mobile edge computing; User authentication; User quality of experience; Quality of service; Mobile computing; Computer networks; Computer security; RADIUS (Computer network protocol)