Efficient Aggregate Queries on Location Data with Confidentiality

Abstract

Location data have great value for facility location selection. Due to the privacy issues of both location data and user identities, a location service provider can not hand over the private location data to a business or a third party for analysis or reveal the location data for jointly running data analysis with a business. In this paper, we propose a newly constructed PSI filter that can help the two parties privately find the data corresponding to the items in the intersection without any computations and, subsequently, we give the PSI filter generation protocol. We utilize it to construct three types of aggregate protocols for facility location selection with confidentiality. Then we propose a ciphertext matrix compressing method, making one block of cipher contain lots of plaintext data while keeping the homomorphic property valid. This method can efficiently further reduce the computation/communication cost of the query process—the improved query protocol utilizing the ciphertext matrix compressing method is given followed. We show the correctness and privacy of the proposed query protocols. The theoretical analysis of computation/communication overhead shows that our proposed query protocols are efficient both in computation and communication and the experimental results of the efficiency tests show the practicality of the protocols.