The autonomous vehicles will make ride sharing popular, and necessary. However, ride sharing organization requires the passengers to reveal sensitive information about their trips, which causes a serious privacy issue. In this paper, we propose a privacy-preserving ride sharing organization scheme using the kNN encryption scheme, Bloom filter, and group signature. Each user encrypts his trip's data and sends an encrypted ride-sharing request to a server that measures the similarity between users trips' to organize shared rides without revealing sensitive information. Comparing to our proposal in [1], this paper has three improvements. The proposed scheme is much more efficient because the trip data is much shorter. It is also more secure because each user has his own encryption key instead of using one shared key for all users. It can prevent linking the encryptions of the trip's data sent at different times because users frequently update their keys efficiently. Our privacy analysis demonstrates that the proposed scheme can preserve users' location privacy and trips' data privacy. Our experimental results on a real map demonstrate that the proposed scheme is much more efficient than the existing schemes, especially for large cities.


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    Title :

    Privacy-Preserving Ride Sharing Organization Scheme for Autonomous Vehicles in Large Cities


    Contributors:


    Publication date :

    2017-09-01


    Size :

    529370 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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