Secure Sharing of Private Locations through Homomorphic Bloom Filters
Yunhe Feng, Zheng Lu, Qing Cao · 2018
Location information is becoming increasingly popular in online social networks, vehicle networks, and online games. In this paper, we develop a distributed protocol that allows one party to determine, in a private and secure manner, whether or not the trajectory of a second party has an intersection with specific locations of interest. Our design is fully flexible, meaning that each user is able to specify what kind of datasets they would like to make visible, and be queried by other users. The methodology is based on developing a generalized set membership check approach, using an advanced data structure called the bloom filter. To demonstrate its feasibility and usability, we offer three working prototypes, which are implemented on the open-source homomorphic libraries. Our preliminary results illustrate the performance and overhead of the proposed approaches as well as the security of the protocol designs.