Outsourcing MPC Precomputation for Location Privacy
Paper in proceeding, 2022

Proximity testing is at the core of sev-eral Location-Based Services (LBS) offered by, e.g., Uber, Facebook, and BlaBlaCar, as it determines closeness to a target. Unfortunately, modern LBS demand not only that clients disclose their locations in plain, but also to trust that the services will not abuse this information. These requirements are unfounded as there are ways to perform proximity testing without revealing one's location. We propose POLAR, a protocol that imple-ments privacy-preserving proximity testing for LBS. POLAR is suitable for clients running mo-bile devices, and relies on a careful combination of three well-established multiparty computation protocols and lightweight cryptography. A point of originality is the inclusion of two servers into the proximity testing. The servers may aid multiple pairs of clients and contribute towards enhancing privacy, improving efficiency, and reducing the run-ning time of clients' procedures.

active security

multi-party computation

privacy

proximity-testing

Author

Ivan Oleinikov

Chalmers, Computer Science and Engineering (Chalmers), Information Security

Elena Pagnin

Lund University

Andrei Sabelfeld

Chalmers, Computer Science and Engineering (Chalmers), Information Security

Proceedings - 7th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2022

504-513
9781665495608 (ISBN)

7th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2022
Genoa, Italy,

Subject Categories

Computer Engineering

Computer Science

Computer Systems

DOI

10.1109/EuroSPW55150.2022.00060

More information

Latest update

7/25/2022