用同态加密实现快速安全的位置查询，保护用户隐私
Versatile and Fast Location-Based Private Information Retrieval with Fully Homomorphic Encryption over the Torus
- 基于环上全同态加密，支持区间、坐标和标识匹配三种查询模式
- 在真实数据集上比之前方法快11.55倍，跨CPU/GPU平台可扩展
- 适合需要隐私保护的定位服务，如紧急预警和位置信息检索
基于位置的服务常需用户共享敏感位置信息，存在被不可信服务器滥用的风险。为此，本文提出VeLoPIR——一种多功能、高效的位置私有信息检索系统，可在保护用户隐私的同时支持大规模查询。该系统包含区间验证、坐标验证和标识匹配三种模式，适用于信息推送与紧急预警等场景。通过多层次算法优化与并行结构设计，系统在CPU和GPU平台上均实现显著可扩展性。我们提供了形式化安全与隐私证明，证实其在标准密码学假设下的安全性。在真实数据集上的大量实验表明，VeLoPIR相比先前基线系统最高提速11.55倍。代码已公开于https://github.com/PrivStatBool/VeLoPIR。
原文摘要 · Abstract (English)
Location-based services often require users to share sensitive locational data, raising privacy concerns due to potential misuse or exploitation by untrusted servers. In response, we present VeLoPIR, a versatile location-based private information retrieval (PIR) system designed to preserve user privacy while enabling efficient and scalable query processing. VeLoPIR introduces three operational modes-interval validation, coordinate validation, and identifier matching-that support a broad range of real-world applications, including information and emergency alerts. To enhance performance, VeLoPIR incorporates multi-level algorithmic optimizations with parallel structures, achieving significant scalability across both CPU and GPU platforms. We also provide formal security and privacy proofs, confirming the system's robustness under standard cryptographic assumptions. Extensive experiments on real-world datasets demonstrate that VeLoPIR achieves up to 11.55 times speed-up over a prior baseline. The implementation of VeLoPIR is publicly available at https://github.com/PrivStatBool/VeLoPIR.
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