The framework and algorithm for preserving user trajectory while using location-based services in IoT-cloud systems

Abstract

Internet of things (IoT) based location-based services (LBS) are playing an increasingly important role in our daily lives. However, since the LBS server may be hacked, malicious or not credible, there is a good chance that interacting with the LBS server may result in loss of privacy.As per journal instruction, author photo and biography are mandatory for this article. Please provide. Thus, protecting user privacy such as the privacy of user location and trajectory is an important issue to be addressed while using LBS. To address this problem, we first construct three kinds of attack models that may expose a user's trajectory or path while the user is sending continuous queries to a LBS server. Then we construct a novel LBS system model for preserving privacy, and propose the k-anonymity trajectory (KAT) algorithm which is suitable for both single query and continuous queries. Different from existing works, the KAT algorithm selects $$k-1$$k-1 dummy locations using the sliding window based k-anonymity mechanism when the user is making single query, and selects $$k-1$$k-1 dummy trajectories using the trajectory select mechanism for continuous queries. We evaluate the effectiveness of our proposed algorithm by conducting simulations for the single-query and continuous-query scenarios. The simulation results show that our proposed algorithm can protect privacy of users better than existing approaches, while incurring a lower time complexity than those approaches.