Privacy-Preserving Cross-Platform Location Sharing Via Private Information Retrieval

The rapid proliferation of lightweight devices such as sensors, BLE tags, and IoT gadgets has accelerated the demand for secure and efficient location sharing across platforms. As device cooperation and data sharing become increasingly prevalent, achieving privacy-preserving cross-platform location sharing poses significant challenges. Existing solutions predominantly rely on centralized infrastructures or single platforms and expose users' queries and stored location data to inference attacks, compromising privacy and security. This paper proposes a privacy-preserving location sharing framework supporting decentralized operations across multiple independent servers. Our system enables users to privately query the location of their lightweight devices across platforms while protecting the confidentiality of queries and location reports. We leverage an LWE-based Private Information Retrieval (PIR) scheme for efficient query generation and response, ensuring strong privacy guarantees. To support dynamic device location reporting, we employ Binary Fuse Filters (BFF) for compact and efficient data insertion and retrieval. Cross-platform compatibility is achieved through standardized client-server interaction models and robust key synchronization mechanisms. Additionally, client collaboration strategies are introduced to enhance data availability and ensure reliable device localization.