A trust evaluation system based on reputation data in Mobile edge computing network

• Published in: Peer-to-peer networking and applications Vol. 13; no. 5; pp. 1744 - 1755
• Main Authors: Deng, Xiaoheng, Liu, Jin, Wang, Leilei, Zhao, Zhihui
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2020; Springer Nature B.V
• Subjects: Cloud computing; Communications Engineering; Computer Communication Networks; Data management; Edge computing; End users; Engineering; Information Systems and Communication Service; Mobile computing; Networks; Nodes; Reputations; Signal,Image and Speech Processing; Special Issue on Emerging Trends on Data Analytics at the Network Edge; Trustworthiness; Wireless networks; Reputation data; Trust evaluation system; Credibility; Mobile edge computing
• ISSN: 1936-6442; 1936-6450
• DOI: 10.1007/s12083-020-00889-3

In recent days, Mobile Edge Computing (MEC) emerges as a new computing paradigm that pushes computing resources towards the edge of the Internet and close to end users and more scholars begin to carry out their different kinds of research under the framework of edge computing. Unlike cloud computing however, edge computing often lacks a centralized security mechanism, which increases the security risks of resource consumers. Therefore, to address security issues for facilitating MEC well, we focus on the establishment of an effective trust evaluation system in this paper. We presented a Reputation-based Trust Evaluation and Management (RTEM) system for a secure and efficient MEC network, wherein the edge servers are adopted to execute reputation data management for mobile edge nodes. In this system, a three-tier trust evaluation framework (identity trust, capability trust, behavior trust) was proposed to ensure the edge nodes that join the network system for service interaction are qualified, capable, and reliable. In order to update and calculate reputation data more accurately, we designed a reputation-based trust evaluation model and evaluated the effectiveness and robustness of our designed model on the OMNeT++ platform. The results show that our proposed mechanism can increase the transaction success rate of the edge network by more than two times compared with the network without trust evaluation mechanism, and perform better than the traditional subject logic (TSL) trust evalaution mechanism.