Cache-Based Privacy Protection Scheme for Continuous Location Query

Entropy (Basel). 2023 Jan 19;25(2):201. doi: 10.3390/e25020201.

Abstract

Users who initiate continuous location queries are prone to trajectory information leakage, and the obtained query information is not effectively utilized. To address these problems, we propose a continuous location query protection scheme based on caching and an adaptive variable-order Markov model. When a user initiates a query request, we first query the cache information to obtain the required data. When the local cache cannot satisfy the user's demand, we use a variable-order Markov model to predict the user's future query location and generate a k-anonymous set based on the predicted location and cache contribution. We perturb the location set using differential privacy, then send the perturbed location set to the location service provider to obtain the service. We cache the query results returned by the service provider to the local device and update the local cache results according to time. By comparing the experiment with other schemes, the proposed scheme in this paper reduces the number of interactions with location providers, improves the local cache hit rate, and effectively ensures the security of the users' location privacy.

Keywords: differential privacy; k-anonymity; location caching; location protection; variable-order Markov model.