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A Privacy-Preserving Secure Framework for Electric Vehicles in IoT Using Matching Market and Signcryption.

Authors :
Kumar, Gulshan
Saha, Rahul
Rai, Mritunjay Kumar
Buchanan, William J.
Thomas, Reji
Geetha, G.
Hoon-Kim, Tai
Rodrigues, Joel J. P. C.
Source :
IEEE Transactions on Vehicular Technology. Jul2020, Vol. 69 Issue 7, p7707-7722. 16p.
Publication Year :
2020

Abstract

The present world of vehicle technology is inclined to develop Electric Vehicles (EVs) with various optimized features. These vehicles need frequent charging which takes a longer time to charge up. Therefore, scheduling of vehicles in charging stations is required. Besides, the information of the EVs and its location is also stored by the charging stations and therefore creates a concern of EV privacy. Various researches are going on to solve these problems; however, an efficient privacy-preserving solution is less practiced till date. In this paper, a framework for Electric Vehicle (EV) charging is discussed. The framework uses the concept of Matching Market to identify a charging station and uses the lattice-based cryptography for secure communications. The matching market considers multiple factors to provide the best allocation of charging station and cryptography ensures security and privacy preservation. The use of lattice-based cryptographic hash SWIFFT avoids heavy computation. This usage of matching market and lattice cryptography, more specifically signcryption for EV charging framework are the highlights of the solution and add-ons to the novel features. Overall, the presented framework is efficient in terms of computation and communication cost, satisfaction ratio, slot ratio, charging latency and load balancing index. The performance metrics are compared with recent developments in this field. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189545
Volume :
69
Issue :
7
Database :
Academic Search Index
Journal :
IEEE Transactions on Vehicular Technology
Publication Type :
Academic Journal
Accession number :
144615803
Full Text :
https://doi.org/10.1109/TVT.2020.2989817