ECQV-Based Lightweight Revocable Authentication Protocol for Electric Vehicle Charging

Author:

Almuhaideb Abdullah M.ORCID,Algothami Sammar S.

Abstract

In the near future, using electric vehicles will almost certainly be required for the sustainability of nature and our planet. The most significant challenge that users are concerned about is the availability of electric vehicle charging stations. Therefore, to maximize the availability of electric vehicle charging stations, we suggest taking benefit from individual sellers who produce renewable energy from their homes or electric vehicle owners who have charging piles installed in their homes. However, energy services that are rapidly being offered by these businesses do not have a trust connection developed with the consumers and stakeholders in these new systems. Exchange of data related to electric vehicles and energy aggregators can be used to identify users’ behavior and compromise their privacy. Consequently, it is necessary to set up a charging system that will guarantee privacy and security. Several electric vehicle charging systems have been proposed to provide security and privacy preservation. However, ensuring anonymity alone is not enough to guarantee protection from reconstructing the victim vehicle’s route by the tracking adversary, even if the exchanged messages are completely anonymous. Furthermore, anonymity should not be absolute in order to protect the system and function as necessary by all entities. In this research, we propose an effective, secure, and privacy-preserving authentication method based on the Elliptic Curve Qu–Vanstone for an electric vehicle charging system. The proposed scheme provides all the necessary requirements and a reauthentication protocol to minimize the overhead of subsequent authentication processes. To create credentials and validate electric vehicles and energy aggregators, the scheme makes use of the Elliptic Curve Qu–Vanstone implicit certificate mechanism. The new protocols give EVs security and privacy while cutting computational time by 95% thanks to reauthentication, as demonstrated by the performance comparison with earlier works.

Funder

SAUDI ARAMCO Cybersecurity Chair at Imam Abdulrahman Bin Faisal University, Saudi Ara-bia

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Information Systems,Management Information Systems

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