Name
Abstract | ||
|---|---|---|
The sensitive information of vehicles is related to location in vehicular networks. Pseudonym change is an effective way to protect the location privacy of vehicles, which is to establish a specific area called mix zone, where at least k number of vehicles change pseudonyms together to obtain k anonymity. However, it depends on the number of collaborative ones in spatiotemporal context. To solve the pseudonym change problem in the low density of vehicles, an independent mix zone scheme, shorted for indMZ, is proposed in this paper. It specifies a pseudonym scheme for the vehicular networks, which consists of the procedures of certification issuance and pseudonym issuance. Each vehicle will have L pseudonyms when it enrolls to a road side units. As a pseudonym is about to be expired, the vehicle can establish a mix zone through beacon messages which are inherently broadcasted in neighborhood periodically. The independent mix zone means that each of the collaborative vehicles will produce some randomized versions of a pseudonym, respectively, and contribute to the desired k-anonymous mix zone. Even in the worst case of zero collaborator, the vehicle can still establish a k anonymous pseudonym change region all by itself. We evaluate indMZ and other mix zone schemes with respective to the performance and strength of location privacy in the low density of vehicular networks. It shows that indMZ can ensure k anonymity with k/2 average cost of extended beacon message and be independent on any trusted third party. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACCESS.2018.2800907 | IEEE ACCESS |
Keywords | Field | DocType |
Vehicular networks,location privacy,mix zone | Trusted third party,Computer science,Pseudonym,Computer network,Average cost,Software,Anonymity,Certification,Information sensitivity,Vehicular ad hoc network | Journal |
Volume | ISSN | Citations |
6 | 2169-3536 | 2 |
PageRank | References | Authors |
0.37 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nan Guo | 1 | 5 | 2.44 |
| Linya Ma | 2 | 2 | 0.37 |
| Tianhan Gao | 3 | 18 | 17.71 |