Trust and reputation management for securing collaboration in 5G access networks: the road ahead

Ahmad, I., Yau, K.-L. A., Mee Hong, L. and Keoh, S. L. (2020) Trust and reputation management for securing collaboration in 5G access networks: the road ahead. IEEE Access, 8, pp. 62542-62560. (doi: 10.1109/ACCESS.2020.2984318)

Abstract

Trust represents the belief or perception of an entity, such as a mobile device or a node, in the extent to which future actions and reactions are appropriate in a collaborative relationship. Reputation represents the network-wide belief or perception of the trustworthiness of an entity. Each entity computes and assigns a trust or reputation value, which increases and decreases with the appropriateness of actions and reactions, to another entity in order to ensure a healthy collaborative relationship. Trust and reputation management (TRM) has been investigated to improve the security of traditional networks, particularly the access networks. In 5G, the access networks are multi-hop networks formed by entities which may not be trustable, and so such networks are prone to attacks, such as Sybil and crude attacks. TRM addresses such attacks to enhance the overall network performance, including reliability, scalability, and stability. Nevertheless, the investigation of TRM in 5G, which is the next-generation wireless networks, is still at its infancy. TRM must cater for the characteristics of 5G. Firstly, ultra-densification due to the exponential growth of mobile users and data traffic. Secondly, high heterogeneity due to the different characteristics of mobile users, such as different transmission characteristics (e.g., different transmission power) and different user equipment (e.g., laptops and smartphones). Thirdly, high variability due to the dynamicity of the entities’ behaviors and operating environment. TRM must also cater for the core features of 5G (e.g., millimeter wave transmission, and device-to-device communication) and the core technologies of 5G (e.g., massive MIMO and beamforming, and network virtualization). In this paper, a review of TRM schemes in 5G and traditional networks, which can be leveraged to 5G, is presented. We also provide an insight on some of the important open issues and vulnerabilities in 5G networks that can be resolved using a TRM framework.

• Item Type: Articles
• Additional Information: This work was part of the project entitled "A Novel Clustering Algorithm based on Reinforcement Learning for the Optimization of Global and Local Network Performances in Mobile Networks" funded by the Malaysian Ministry of Education under Fundamental Research Grant Scheme FRGS/1/2019/ICT03/SYUC/01/11.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Keoh, Dr Sye Loong
• Authors: Ahmad, I., Yau, K.-L. A., Mee Hong, L., and Keoh, S. L.
• College/School: College of Science and Engineering > School of Computing Science
• Research Group: GLASS
• Journal Name: IEEE Access
• Publisher: IEEE
• ISSN: 2169-3536
• ISSN (Online): 2169-3536
• Published Online: 30 March 2020
• Copyright Holders: Copyright © 2020 The Authors
• First Published: First published in IEEE Access 8: 62542-62560
• Publisher Policy: Reproduced under a Creative Commons License