Anonymity Assurance Using Efficient Pseudonym Consumption in Internet of Vehicles.

BSM IoVs adversary pseudonym consumption traceability vehicle anonymization

Journal

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

Informations de publication

Date de publication:
31 May 2023
Historique:
received: 06 03 2023
revised: 24 04 2023
accepted: 23 05 2023
medline: 12 6 2023
pubmed: 10 6 2023
entrez: 10 6 2023
Statut: epublish

Résumé

The Internet of vehicles (IoVs) is an innovative paradigm which ensures a safe journey by communicating with other vehicles. It involves a basic safety message (BSM) that contains sensitive information in a plain text that can be subverted by an adversary. To reduce such attacks, a pool of pseudonyms is allotted which are changed regularly in different zones or contexts. In base schemes, the BSM is sent to neighbors just by considering their speed. However, this parameter is not enough because network topology is very dynamic and vehicles can change their route at any time. This problem increases pseudonym consumption which ultimately increases communication overhead, increases traceability and has high BSM loss. This paper presents an efficient pseudonym consumption protocol (EPCP) which considers the vehicles in the same direction, and similar estimated location. The BSM is shared only to these relevant vehicles. The performance of the purposed scheme in contrast to base schemes is validated via extensive simulations. The results prove that the proposed EPCP technique outperformed compared to its counterparts in terms of pseudonym consumption, BSM loss rate and achieved traceability.

Identifiants

pubmed: 37299944
pii: s23115217
doi: 10.3390/s23115217
pmc: PMC10256095
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : King Saud University
ID : RSPD2023R521

Références

Sensors (Basel). 2019 Jan 15;19(2):
pubmed: 30650658
Sensors (Basel). 2021 Apr 01;21(7):
pubmed: 33916309
Sensors (Basel). 2021 Apr 28;21(9):
pubmed: 33925131

Auteurs

Mehreen Mushtaq (M)

Department of Computer Science, National University of Modern Languages (NUML), Islamabad 44000, Pakistan.

Ata Ullah (A)

Department of Computer Science, National University of Modern Languages (NUML), Islamabad 44000, Pakistan.

Humaira Ashraf (H)

Department of Computer Science and Software Engineering, International Islamic University Islamabad, Islamabad 44000, Pakistan.

N Z Jhanjhi (NZ)

School of Computer Science SCS, Taylor's University, Subang Jaya 47500, Malaysia.

Mehedi Masud (M)

Department of Computer Science, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia.

Abdulmajeed Alqhatani (A)

Department of Information Systems, College of Computer Science & Information Systems, Najran University, Najran 61441, Saudi Arabia.

Mrim M Alnfiai (MM)

Department of Information Technology, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia.

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