IMF-PR: An Improved Morton-Filter-Based Pseudonym-Revocation Scheme in VANETs.
CRL
VANETs
improved Morton filter
pseudonym revocation
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
18 Apr 2023
18 Apr 2023
Historique:
received:
14
03
2023
revised:
04
04
2023
accepted:
12
04
2023
medline:
28
4
2023
pubmed:
28
4
2023
entrez:
28
4
2023
Statut:
epublish
Résumé
Vehicle ad hoc networks (VANETs) are special wireless networks which help vehicles to obtain continuous and stable communication. Pseudonym revocation, as a vital security mechanism, is able to protect legal vehicles in VANETs. However, existing pseudonym-revocation schemes suffer from the issues of low certificate revocation list (CRL) generation and update efficiency, along with high CRL storage and transmission costs. In order to solve the above issues, this paper proposes an improved Morton-filter-based pseudonym-revocation scheme for VANETs (IMF-PR). IMF-PR establishes a new distributed CRL management mechanism to maintain a low CRL distribution transmission delay. In addition, IMF-PR improves the Morton filter to optimize the CRL management mechanism so as to improve CRL generation and update efficiency and reduce the CRL storage overhead. Moreover, CRLs in IMF-PR store illegal vehicle information based on an improved Morton filter data structure to improve the compress ratio and the query efficiency. Performance analysis and simulation experiments showed that IMF-PR can effectively reduce storage by increasing the compression gain and reducing transmission delay. In addition, IMF-PR can also greatly improve the lookup and update throughput on CRLs.
Identifiants
pubmed: 37112407
pii: s23084066
doi: 10.3390/s23084066
pmc: PMC10145359
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