MATEC Web Conf.
Volume 355, 20222021 International Conference on Physics, Computing and Mathematical (ICPCM2021)
|Number of page(s)||10|
|Section||Computing Methods and Computer Application|
|Published online||12 January 2022|
An efficient anonymous group handover authentication protocol for MTC devices for 5G networks
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
* Corresponding author: email@example.com
Machine Type Communication (MTC) has been emerging for a wide range of applications and services for the Internet of Things (IoT). In some scenarios, a large group of MTC devices (MTCDs) may enter the communication coverage of a new target base station simultaneously. However, the current handover mechanism specified by the Third Generation Partnership Project (3GPP) incur high signalling overhead over the access network and the core network for such scenario. Moreover, other existing solutions have several security problems in terms of failure of key forward secrecy (KFS) and lack of mutual authentication. In this paper, we propose an efficient authentication protocol for a group of MTCDs in all handover scenarios. By the proposal, the messages of two MTCDs are concatenated and sent by an authenticated group member to reduce the signalling cost. The proposed protocol has been analysed on its security functionality to show its ability to preserve user privacy and resist from major typical malicious attacks. It can be expected that the proposed scheme is applicable to all kinds of group mobility scenarios such as a platoon of vehicles or a high-speed train. The performance evaluation demonstrates that the proposed protocol is efficient in terms of computational and signalling cost.
Key words: Group handover authentication / MTCD / 5G / Privacy-preserving
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.