Privacy-Preserving Location Sharing via LWE-based Private Information Retrieval
Qingshui Xue, Tianrui Cui · 2023
We proposes a privacy-preserving location sharing scheme based on Learning with Errors (LWE) encryption, emphasizing its ability to resist quantum computing attacks and provide a high level of security. In order for real-world usage, we focus on its efficiency, flexibility, and adaptability for streaming. Location privacy has has emerged as a critical concern in today's data-driven society, due to the widespread usage of location-based services and the growing demand for personalized information. We leverages for fast and accurate information retrieval while maintaining robust privacy guarantees, achieving peer-to-peer transmission, 128-bit security or higher and an unparalleled throughput of 10 GB/s/core Through extensive experimental evaluations conducted on real-world deployments, we demonstrate the remarkable performance of our scheme in terms of preserving privacy and retrieval speed, particularly for streaming location data.