A dual mode privacy-preserving scheme enabled secure and anonymous for edge computing assisted internet of vehicle networks

Han, Xu, Tian, Daxin, Duan, Xuting, Sheng, Zhengguo, Zhou, Jianshan and Leung, Victor C M (2021) A dual mode privacy-preserving scheme enabled secure and anonymous for edge computing assisted internet of vehicle networks. MSWiM '21: 24th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Spain, 22nd - 26th November 2021. Published in: DIVANet '21: Proceedings of the 11th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications. 65-70. ACM, New York, NY, United States. ISBN 9781450390774

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Abstract

This paper adopts Named Data Network technology for data delivery/forwarding over the Internet of Vehicles (IoVs) and proposes an NDN-based architecture for IoVs based on mobile edge computing(MEC). Advanced research has demonstrated the considerable benefits of introducing MEC into IoVs, but comes with issues such as insufficient security and privacy protection problems. To address these issues, we propose a dual-mode privacy-preserving framework for the security layer of the proposed network architecture. Specifically, we construct a privacy protection identity-based broadcast proxy re-encryption scheme to provide privacy to a set of vehicles with data requests. Furthermore, we use a federated learning scheme based on local differential privacy in the proposed NDN-based architecture for MEC-empowered IoV to achieve high-speed response and decision making. Simulation results demonstrate that our proposed scheme performs effectively.

Item Type: Conference Proceedings
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 04 Mar 2022 10:59
Last Modified: 04 Mar 2022 12:12
URI: http://sro.sussex.ac.uk/id/eprint/104693

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