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Anonymization Based Location Privacy Preservation in Vehicular Ad Hoc Networks

The Vehicular Adhoc Networks (VANETs) are used for many safety related applications like accident avoidance, controlling traffic and emergency warning. All these applications require vehicles to broadcast their position, velocity, direction and identity during fixed intervals. It becomes necessary to preserve the location privacy of the vehicle since global attackers can collect obtain these values and misuse them. In this paper, a more robust and scalable approach for privacy preservation based on t-closeness model is proposed. By experimental analysis, it is inferred that even when the number of vehicles in a lane increases, the information gained by the observer is less in t-closeness model when compared to the previous k-anonymity model.