Privacy-Preserving Location-Based Services by using Intel SGX

We are witnessing a rapid proliferation of location-based services, due to the useful context-aware services they provide their users. However, sharing sensitive location traces with untrusted service-providers has many privacy implications. Although, user-data monetization is the core economic model of such services, offering private services to concerned users will be a beneficial functionality in the coming years. Existing solutions include location perturbation, k-anonymity and cryptographic primitives that trade service accuracy or latency for enhanced user privacy. We introduce a novel approach for privacy preserving location-based services by using the Intel Software Guard eXtensions (SGX). We implement a simple location-based service using SGX and gauge its performance in terms of efficiency and effectiveness, in comparison with its bare-metal implementation. Our evaluation results show that SGX contributes a marginal overhead but also provides near-to-the-perfect results in contrast to spatial cloaking with k-anonymity whose performance deteriorates as the degree of desired privacy increases. We show that hardware-based trusted execution-environments are a promising alternative for offering proactive and de-facto location-privacy in the context of location-based services.