TriNymAuth: Triple Pseudonym Authentication Scheme for VANETs Based on Cuckoo Filter and Paillier Homomorphic Encryption.

Paillier homomorphic encryption VANETs cuckoo filter identity authentication privacy protection

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
19 Jan 2023
Historique:
received: 30 10 2022
revised: 16 12 2022
accepted: 19 12 2022
entrez: 11 2 2023
pubmed: 12 2 2023
medline: 12 2 2023
Statut: epublish

Résumé

In VANETs, owing to the openness of wireless communication, it is necessary to change pseudonyms frequently to realize the unlinkability of vehicle identity. Moreover, identity authentication is needed, which is usually completed by digital certificates or a trusted third party. The storage and the communication overhead are high. This paper proposes a triple pseudonym authentication scheme for VANETs based on the Cuckoo Filter and Paillier homomorphic encryption (called TriNymAuth). TriNymAuth applies Paillier homomorphic encryption, a Cuckoo Filter combining filter-level and bucket-level, and a triple pseudonym (homomorphic pseudonym, local pseudonym, and virtual pseudonym) authentication to the vehicle identity authentication scheme. It reduces the dependence on a trusted third party and ensures the privacy and security of vehicle identity while improving authentication efficiency. Experimental results show that the insert overhead of the Cuckoo Filter is about 10 μs, and the query overhead reaches the ns level. Furthermore, TriNymAuth has significant cost advantages, with an OBU enrollment cost of only 0.884 ms. When the data rate in VANETs dr≤ 180 kbps, TriNymAuth has the smallest total transmission delay cost and is suitable for shopping malls and other places with dense traffic.

Identifiants

pubmed: 36772204
pii: s23031164
doi: 10.3390/s23031164
pmc: PMC9918982
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Natural Science Foundation of China
ID : 52130403
Organisme : Fundamental Research Funds for the Central Universities
ID : N2017003

Auteurs

Luyuan Zhuang (L)

Computer Science & Engineering College, Northeastern University, Shenyang 110167, China.

Nan Guo (N)

Computer Science & Engineering College, Northeastern University, Shenyang 110167, China.

Yufan Chen (Y)

Computer Science & Engineering College, Northeastern University, Shenyang 110167, China.

Classifications MeSH