Abstract:

To solve the issue of mobile terminal users’ trajectory privacy security and individualized needs in location-based services, a k anonymous trajectory privacy protection scheme based on individualized differential privacy is proposed. The proposed scheme first allocates different privacy budgets according to individual differences, then adopts differential privacy technology to repeatedly add laplacian noise to the user trajectory to generate 2k noise trajectories. After that, it uses the trajectory similarity measurement method to determine the optimal k-1 noise users, which form k anonymous user groups in combination with real users, and then randomly selects a proxy user to replace the real user to perform location-based services requests to realize the privacy protection of user identities and trajectories. Security analysis shows that the scheme satisfies anonymity such security features as anonymity, unforgeability, and anti-counterfeiting attack. Simulation results show that the scheme not only has an obvious advantage in privacy protection but also has high execution efficiency.

Key words: differential privacy, k-anonymous, trajectory privacy, location based services