InnerCircle: A Parallelizable Decentralized Privacy-Preserving Location Proximity Protocol
Paper in proceedings, 2015

Location Based Services (LBS) are becoming increasingly popular. Users enjoy a wide range of services from tracking a lost phone to querying for nearby restaurants or nearby tweets. However, many users are concerned about sharing their location. A major challenge is achieving the privacy of LBS without hampering the utility. This paper focuses on the problem of location proximity, where principals are willing to reveal whether they are within a certain distance from each other. Yet the principals are privacy-sensitive, not willing to reveal any further information about their locations, nor the distance. We propose InnerCircle, a novel secure multi-party computation protocol for location privacy, based on partially homomorphic encryption. The protocol achieves precise fully privacy-preserving location proximity without a trusted third party in a single round trip. We prove that the protocol is secure in the semi-honest adversary model of Secure Multi-party Computation, and thus guarantees the desired privacy properties. We present the results of practical experiments of three instances of the protocol using different encryption schemes. We show that, thanks to its parallelizability, the protocol scales well to practical applications.

Author

Per Hallgren

Chalmers, Computer Science and Engineering (Chalmers), Software Technology (Chalmers)

Martin Ochoa

Technical University of Munich

Andrei Sabelfeld

Chalmers, Computer Science and Engineering (Chalmers), Software Technology (Chalmers)

Proceedings of the International Conference on Privacy, Security and Trust (PST)

1-6

Areas of Advance

Information and Communication Technology

Subject Categories

Computer and Information Science

Roots

Basic sciences

DOI

10.1109/PST.2015.7232947

More information

Latest update

10/30/2019