Stealth Friend Locator: Server Blinded Private Location Sharing
Tyler Nicewarner, Ali Ataeemh Allami, Dan Lin · 2025
The widespread use of family tracing apps has highlighted the need for effective location privacy protection. Unfortunately, current solutions fail to provide stringent privacy protection or are computationally expensive, making them unsuitable for real-time services. In this paper, we propose a highly efficient system architecture that supports three common types of location-sharing queries (i.e., point queries, range queries, and k nearest neighbor queries) with strict privacy protection. The proposed design is based on the envisioned future collaborations between two social media platforms. One platform manages location privacy policies, while the other facilitates location collection and sharing requests. Our main contributions involve two new privacy-preserving query protocols. One is a highly efficient, generic secure comparison protocol for range queries. The other is a novel kNN query protocol that eliminates the need for computationally expensive secure sorting in existing solutions, thus offering unparalleled performance without compromising security. The paper provides a formal and rigorous security analysis of the proposed solutions using the Universally Composable framework. We also conduct extensive experiments that demonstrate that our approach is more than an order of magnitude faster than existing solutions.