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author:

Zhang, Chuan (Zhang, Chuan.) [1] | Zhu, Liehuang (Zhu, Liehuang.) [2] | Xu, Chang (Xu, Chang.) [3] | Sharif, Kashif (Sharif, Kashif.) [4] | Ding, Kai (Ding, Kai.) [5] | Liu, Ximeng (Liu, Ximeng.) [6] | Du, Xiaojiang (Du, Xiaojiang.) [7] | Guizani, Mohsen (Guizani, Mohsen.) [8]

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EI

Abstract:

Vehicle platoon, a novel vehicle driving paradigm that organizes a group of vehicles in the nose-to-tail structure, has been considered as a potential solution to reduce traffic congestion and increase travel comfort. In such a platoon system, head vehicles' performances are usually evaluated by user vehicles' feedbacks. Selection of an appropriate and reliable head vehicle while not disclosing user vehicles' privacy has become an interesting problem. In this article, we present a trust-based and privacy-preserving platoon recommendation scheme, called TPPR, to enable potential user vehicles to avoid selecting the malicious head vehicles. The basic concept of TPPR is that each user vehicle holds a trust value, and the reputation score of the head vehicle is calculated via a truth discovery process. To preserve vehicles' privacy, pseudonyms and Paillier cryptosystem are applied. In addition, novel authentication protocols are designed to ensure that only the valid vehicles (i.e., the vehicles holding the truthful trust values and joining the vehicle platoon) can pass the authentication. A comprehensive security analysis is conducted to prove that the proposed TPPR scheme is secure against several sophisticated attacks in vehicular ad hoc networks. Moreover, extensive simulations are conducted to demonstrate the correctness and effectiveness of the proposed scheme. © 2008-2012 IEEE.

Keyword:

Authentication Traffic congestion Vehicles Vehicular ad hoc networks

Community:

  • [ 1 ] [Zhang, Chuan]Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application, School of Computer Science and Technology, Beijing Institute of Technology, Beijing; 100811, China
  • [ 2 ] [Zhu, Liehuang]Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application, School of Computer Science and Technology, Beijing Institute of Technology, Beijing; 100811, China
  • [ 3 ] [Xu, Chang]Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application, School of Computer Science and Technology, Beijing Institute of Technology, Beijing; 100811, China
  • [ 4 ] [Sharif, Kashif]Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application, School of Computer Science and Technology, Beijing Institute of Technology, Beijing; 100811, China
  • [ 5 ] [Ding, Kai]Beijing Eng. Res. Center of Massive Language Information Processing and Cloud Computing Application, School of Computer Science and Technology, Beijing Institute of Technology, Beijing; 100811, China
  • [ 6 ] [Liu, Ximeng]School of Information Systems, Singapore Management University, College of Mathematics and Computer Science, Fuzhou University, Fujian, Fuzhou; 350002, China
  • [ 7 ] [Du, Xiaojiang]Department of Computer and Information Sciences, Temple University, Philadelphia; PA; 19122, United States
  • [ 8 ] [Guizani, Mohsen]Department of Computer Science and Engineering, Qatar University, Doha; 2713, Qatar

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Source :

IEEE Transactions on Services Computing

Year: 2022

Issue: 2

Volume: 15

Page: 806-818

8 . 1

JCR@2022

5 . 5 0 0

JCR@2023

ESI HC Threshold:61

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 31

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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