Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/166640
Title: Effective authentication to prevent Sybil attacks in vehicular platoons
Authors: Junaidi, Danial Ritzuan
Ma, Maode
Su, Rong
Keywords: Engineering::Electrical and electronic engineering::Wireless communication systems
Issue Date: 2022
Source: Junaidi, D. R., Ma, M. & Su, R. (2022). Effective authentication to prevent Sybil attacks in vehicular platoons. 2022 17th International Conference on Control, Automation, Robotics and Vision (ICARCV), 949-954. https://dx.doi.org/10.1109/ICARCV57592.2022.10004350
Project: A19D6a0053 
Conference: 2022 17th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Abstract: The potential ability to increase the capacity and safety on roads, as well as fuel economy gains has made vehicle platooning an appealing prospect. However, its use is yet to be widespread, partially due to the security concerns on it. One particular concern is the admission of fake virtual vehicles into the platoons, allowing them to wreak havoc on the platoon, which is known as a Sybil attack. In this paper, we propose a secure vehicular authentication scheme for platoon admission which is resistant to the threats of Sybil attacks. The proposed scheme offers a mutual authentication on both vehicle identity and message through a combination of a key exchange, a digital signature and an encryption scheme based on Elliptic Curve Cryptography (ECC). The scheme holds its outstanding feature to provide both perfect forward secrecy and group backward secrecy to ensure the protection of anonymity of vehicles and platoons while typical malicious attacks such as replay, and man-in-the-middle attacks can also be resisted. A formal evaluation of the security of the scheme by Canetti-Krawczyk (CK) adversary and random oracle model has been conducted to demonstrate its security functionality. Finally, the performance of the proposed scheme has been evaluated to show its efficiency.
URI: https://hdl.handle.net/10356/166640
ISBN: 9781665476874
DOI: 10.1109/ICARCV57592.2022.10004350
Schools: School of Electrical and Electronic Engineering 
Rights: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICARCV57592.2022.10004350.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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