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. 2023 Apr 18;23(8):4066.
doi: 10.3390/s23084066.

IMF-PR: An Improved Morton-Filter-Based Pseudonym-Revocation Scheme in VANETs

Cong Zhao  1 , Jiayu Qi  1 , Tianhan Gao  1 , Xinyang Deng  1
Affiliations

IMF-PR: An Improved Morton-Filter-Based Pseudonym-Revocation Scheme in VANETs

Cong Zhao et al. Sensors (Basel). .

Abstract

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.

Keywords: CRL; VANETs; improved Morton filter; pseudonym revocation.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 2
Figure 2
Morton filter.
Figure 4
Figure 4
Improved Morton filter.
Figure 7
Figure 7
Remove the expired pseudonym and fingerprint algorithm.
Figure 1
Figure 1
VANET architecture.
Figure 3
Figure 3
IMF-PR system architecture.
Figure 5
Figure 5
IMF-CRL.
Figure 6
Figure 6
The flow diagram of the proposed scheme.
Figure 8
Figure 8
Insert the new pseudonym and fingerprint algorithm.
Figure 9
Figure 9
Compression gain (α = 0.5).
Figure 10
Figure 10
Compression gain (α = 0.8).
Figure 11
Figure 11
Transmission delay (α = 0.5, ϵ=0.1%).
Figure 12
Figure 12
Query throughput.
Figure 13
Figure 13
Update throughput. (α = 0.5).
See this image and copyright information in PMC

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