TAPCS: Traffic-aware pseudonym changing strategy for VANETs

Boualouache, Abdelwahab; Moussaoui, Samira

doi:10.1007/s12083-016-0461-4

Cited by 35 publications

(34 citation statements)

References 27 publications

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“…The reason is that, in the first case, all the neighbors that have WCP flags set to 1 change their pseudonyms with the target vehicle, while in the second case some of those neighbors are malicious, which decreases significantly the average ASS of the target vehicle, which is obtained by computing the average of the cardinality of the honest neighbors set of the target vehicle. Moreover, with the increasing adversary attendance rate up to 50%, we can see that the average ASS value of the target vehicle lowers down, because of the increased number of malicious neighbors around the target vehicle, causing a decrease in the number of honest neighbors, which in turn reduces the average ASS of the target vehicle A,B,C shows the average anonymity set sif of target various traffic density scenarios; our method is low set sif of target compared with existing methods low, medium, and high traffic density scenario; it means that our method is outperformed compare with existing methods …”

Section: Resultsmentioning

confidence: 78%

“…This is explained by the fact that the malicious vehicles (in this scenario, the adversary attendance rate is 15%) abstain from changing their pseudonyms with the rest of the AS elements. Figure A,B,C shows that the number of cheating attack increases while time increases with various traffic density environment .other words, the number of vehicles increases also increases probability changing pseudonyms due to decreases attacker guess probability …”

Section: Resultsmentioning

confidence: 89%

“…Figure C message loss ratio versus time, when the time is increases message loss ratio decreases due to the number of cooperative vehicles change the pseudonyms. Figure D shows that the number of road side unit increases also increases the area coverage and increases number of pseudonyms …”

Section: Resultsmentioning

confidence: 99%

“…The above equation represents the information loss with different number of trajectories, Area { S ( O i , t j )} represents the area size of the generalized regions of O i at time t j , T is the number of trajectories, and n is the number of timestamps in anonymity regions. Based on the definition of information loss, we compare our proposed method with some previous proposals such as PMS, Mixgroup technique, and TAPCS as follows.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, in all safety apps and mostly in delay tolerant networks, message dissemination performs a very important role for the sake of quality of service. Additionally, data dissemination in traffic‐based applications will always be an issue in road networks . Moreover, the main advantage of these applications would be of public benefit rather than for individual basis.…”

Section: Related Workmentioning

confidence: 99%

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Pseudonym changing strategy with multiple mix zones for trajectory privacy protection in road networks

Memon

Chen

Arain

et al. 2017

Int J Communication

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SummaryIn road network, vehicles' location may be identified, and their transmissions may even tracked by eavesdrops (eg, safety messages) that contain sensitive personal information such as identity and location of the vehicle. This type of communication leads to breaking the users' trajectory privacy. Frequently changing pseudonyms are widely accepted as a solution that protects the trajectory privacy of users in road networks. However, this solution may become invalid if a vehicle changes its pseudonym at an improper occasion. To cope with this issue, we presented an efficient pseudonym change strategy with multiple mix zones scheme to provide trajectory privacy for road network. In addition, we protected vehicles against linkability attack by cheating mechanism. Henceforth, we constructed a cheating detection mechanism which allows the vehicles to verify whether the pseudonym change process is successful or not and also detect to malicious vehicles. In this way, users' trajectory privacy can be improved. Finally, by taking the anonymity set size (ASS) as the trajectory privacy metric, we exhibit by means of simulations that the proposed scheme is effective in multiple networks scenarios. KEYWORDS changing pseudonyms, cheating detection, cooperation, multiple mix-zones security, road networks, silent period, trajectory privacy | INTRODUCTIONRoad networks consist of vehicles and road-side units (RSUs) equipped with radio transceivers. Vehicles communicate with each other using vehicle-to-vehicle (V2V) communications, and with RSUs using vehicle-to-infrastructure (V2I) communications. 1 Road network promises safer driving conditions and more efficient traffic management. For safety applications, several initiatives have been launched to draw strong support in Europe 2,3 and also USA. 4 Road network offers a wide range of applications. We distinguish typically 2 classes of applications: (1) safety applications and (2) non-safety applications. Safety applications allow vehicles to exchange safety-related information in order to prevent accidents and hazardous situations. For example, such applications included cooperative driving, collision avoidance warnings, etc. Non-safety applications, such as Internet access, point of interest notification, and infotainment, focus on providing convenience and entertainment to drivers and passengers.In order to achieve road network applications, vehicles are required to broadcast periodic beacons into their direct neighborhood and occasionally event-based messages (eg, safety messages) as shown in Figure 1. These messages reported sensitive personal information about their senders such as the identity and location of the vehicle. 5 Due to

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Section: Resultsmentioning

confidence: 78%

Section: Resultsmentioning

confidence: 89%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

Pseudonym changing strategy with multiple mix zones for trajectory privacy protection in road networks

Memon

Chen

Arain

et al. 2017

Int J Communication

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References

2022

Security in Vehicular Networks

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Privacy‐preserving multilevel obfuscation scheme for vehicular network

Ullah

Shah

Khan

et al. 2020

Trans Emerging Tel Tech

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For accessing various location‐based services (LBS), a device needs to update its location frequently. The vehicle requires to exchange location messages with LBS while moving on the road network. These messages contain sensitive information of vehicles, that is, location, identity, direction, and other contents. LBS is not trusted and may conspire with an adversary to capture the location messages and based on the location information the adversary tracks the future location spots of the vehicle driver. Existing location privacy schemes require the collaboration of neighbor vehicles to anonymize their location. However, such collaboration needs the consent of the neighbor vehicles. In addition, the messages exchanged with LBS contain the real identity of a vehicle and the vehicle is exposed to identity threat. In this article, we propose a multilevel location privacy scheme (MLPS) for a vehicle using location services. The vehicle generates duplicate messages by taking location positions of transmission range vehicles to anonymize its location and identity. We simulate the proposed scheme for various vehicle traffic densities. The simulation results show that the proposed scheme MLPS is more efficient than the existing scheme in terms of anonymity set size, location obfuscation, and location traceability. The MLPS reduces the vehicle location traceability from 50% to 1% compared with the existing scheme.

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TAPCS: Traffic-aware pseudonym changing strategy for VANETs

Cited by 35 publications

References 27 publications

Pseudonym changing strategy with multiple mix zones for trajectory privacy protection in road networks

Pseudonym changing strategy with multiple mix zones for trajectory privacy protection in road networks

References

Privacy‐preserving multilevel obfuscation scheme for vehicular network

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