CRApr 26, 2018

NEXUS: Using Geo-fencing Services without revealing your Location

arXiv:1804.09933v12 citations
Originality Highly original
AI Analysis

This addresses privacy concerns for users of location-based services, offering a novel solution to a known bottleneck in geo-fencing.

The paper tackles the problem of location privacy in geo-fencing services by proposing a protocol based on homomorphic encryption to keep users' locations secret while providing exact results, provably ensuring full location-privacy without degrading service quality.

While becoming more and more present in our every day lives, services that operate on users' locations or location trajectories suffer from general fear of misappropriation of the transmitted location data. Several works have investigated of how to cope with this drawback. Respective systems claim location-privacy, i.e. keeping users' locations secret, by employing anonymisation techniques concerning a user's identity, or by obfuscating the transmitted location. These approaches lead to a degrade of quality-of-service and can be vulnerable to de-anonymisation attacks, or allow to learn at least the approximate location of a user. Focusing on the application domain of geo-fencing, we present as remedy a protocol that is based on homomorphic encryption of a user's location. The protocol provably provides full location-privacy by non-exposure of the users' location data, while producing exact geo-fencing results. We provide a detailed definition of the protocol, show its applicability in an actual geo-fencing application, and show that the resulting system fulfills all security properties we see for a location-privacy preserving system.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes