云计算中安全的向量点积计算

安全问题是云计算研究的关键问题之一.提出云计算模型中安全的向量点积计算方案，同时提供计算结果的正确性验证和数据的隐私保护功能.通过分析向量和向量点积的代数性质，为数据所有者端的原始向量构建转换向量和影子向量，使客户能够验证计算结果的正确性.将现有两方间隐私保护的向量点积计算协议扩展到云计算模型中的三方.安全性分析表明该方案能够抵御多种可能的威胁.实验结果表明了该方案的高效性.

Secure Scalar Product Computation of Vectors in Cloud Computing

The security problem is one of the key issues of cloud computing research. A secure scalar product computation scheme of vectors was presented in the cloud computing model， which provided correctness verification for computation result and privacy preservation for data simultaneously. Based on the algebraic properties of vector and scalar product of vectors， the transformation vector and mirror vector were constructed for the original vector， which enabled the client to verify the correctness of the computation results. The existing privacy preserving scalar product computation protocol of vectors between two parties was extended to three parties in the cloud computing model. Security analysis demonstrated that the scheme could resist a variety of possible threats. Experimental results showed the efficiency of the scheme.