云环境下基于秘密共享的安全外包主成分分析方案

A Principal Component Analysis Scheme for Security Outsourcing in Cloud Environment Based on Secret Sharing

主成分分析技术的计算开销较大,本地设备一般无法负担,常需要将计算任务进行外包,而外包计算的数据安全问题已成为云计算安全领域的一个研究热点。文章提出一种云环境下基于秘密共享的安全外包主成分分析方案,该方案基于加法秘密共享技术,设计了安全除法和安全平方根计算协议。通过两台云服务器协同执行协方差矩阵、Lanczos、Householder等安全协议计算,实现了主成分分析安全外包计算。与其他安全外包计算方案相比,文章所提方案可以更好地支持客户端离线和多方数据聚合,其计算开销更小,并通过实验验证了方案的有效性。

The computational overhead of principal component analysis is so high that local devices cannot afford it and often require secure outsourcing of computational tasks.The data security issue in outsourcing computation has gradually become a difficult point for cloud computing security research.This paper proposed a secure outsourcing scheme based on secret sharing in cloud environment,which was based on additive secret sharing technology and designed with secure division and secure square root computation protocols.The PCA secure outsourcing computation could be finished by two cloud servers collaboratively performing the covariance matrix,Lanczos,Householder and other secure protocols.Compared with other secure outsourcing computation schemes,this scheme can better support client offline and multi-party data aggregation with better computational overhead,and the experiments verified the effectiveness of the scheme.