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author:

Zhan, Yonghua (Zhan, Yonghua.) [1] | Xie, Weipeng (Xie, Weipeng.) [2] | Shi, Rui (Shi, Rui.) [3] | Huang, Yunhu (Huang, Yunhu.) [4] | Zheng, Xianghan (Zheng, Xianghan.) [5] (Scholars:郑相涵)

Indexed by:

EI Scopus SCIE

Abstract:

Secure group communication in Vehicle Ad hoc Networks (VANETs) over open channels remains a challenging task. To enable secure group communications with conditional privacy, it is necessary to establish a secure session using Authenticated Key Agreement (AKA). However, existing AKAs suffer from problems such as cross-domain dynamic group session key negotiation and heavy computational burdens on the Trusted Authority (TA) and vehicles. To address these challenges, we propose a dynamic privacy-preserving anonymous authentication scheme for condition matching in fog-cloud-based VANETs. The scheme employs general Elliptic Curve Cryptosystem (ECC) technology and fog-cloud computing methods to decrease computational overhead for On-Board Units (OBUs) and supports multiple TAs for improved service quality and robustness. Furthermore, certificateless technology alleviates TAs of key management burdens. The security analysis indicates that our solution satisfies the communication security and privacy requirements. Experimental simulations verify that our method achieves optimal overall performance with lower computational costs and smaller communication overhead compared to state-of-the-art solutions.

Keyword:

authenticated key agreement conditional privacy-preserving dynamic group fog-cloud computing VANETs

Community:

  • [ 1 ] [Zhan, Yonghua]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 2 ] [Xie, Weipeng]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 3 ] [Zheng, Xianghan]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China
  • [ 4 ] [Shi, Rui]Beijing Elect Sci & Technol Inst, Beijing 100070, Peoples R China
  • [ 5 ] [Huang, Yunhu]Minjiang Univ, Comp & Data Sci, Fuzhou 350108, Peoples R China

Reprint 's Address:

  • 谢维鹏

    [Xie, Weipeng]Fuzhou Univ, Coll Comp & Data Sci, Fuzhou 350108, Peoples R China;;[Huang, Yunhu]Minjiang Univ, Comp & Data Sci, Fuzhou 350108, Peoples R China

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SENSORS

ISSN: 1424-8220

Year: 2024

Issue: 6

Volume: 24

3 . 4 0 0

JCR@2023

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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