基于匿名指纹集的室内指纹定位隐私保护算法

Anonymous fingerprint set based privacy preserving scheme for indoor localization

基于Wi-Fi无线信号的指纹定位技术是实现室内定位、追踪等物联网相关应用的重要手段之一。在用户向服务器请求定位服务的同时,如何保护用户的定位隐私和服务器的数据安全是其商业化应用中亟需解决的重要问题。针对目前通过加密算法进行隐私保护时,算法的实时性不足和定位精度不高的问题,设计了一种具有隐私保护的轻量级室内指纹定位算法。采用k匿名算法保护用户的请求隐私,Paillier同态加密算法保护用户的定位隐私和服务器的数据隐私;通过独特的指纹请求子集设计,改进方案进一步降低了定位中的计算开销和通信开销,并实现了定位精度的提升。理论分析和实验研究均表明,所提方案在实现隐私保护的同时,克服了现有同态加密巨大的计算开销问题,并提高了定位性能。

Wi-Fi based fingerprinting localization is one of the promising methods in indoor localization,tracking and other IoT related applications.A common concern is how to prevent the leakage of the client’s location information and data of the localization service provider(LSP)while clients request servers from the LSP.To address the current issues of low real-time perfor-mance and positioning accuracy when privacy preserving is performed by encryption algorithm,this paper proposed a lightweight privacy preserving scheme for fingerprinting localization,which protected the client’s query from LSP with k-anonymity approach and the query answer of the client and LSP’s database information with Paillier homomorphic encryption with low cost.With the unique design of request subsets,the enhanced schemes further reduced the computation overhead and communication cost in the localization query and achieved the improvement of the localization accuracy.Theoretical analysis and experimental results show that the proposed scheme not only achieves privacy preserving while overcoming the huge computational overhead of existing homomorphic encryption,but also improves the localization performance.