A New Efficient Privacy-Preserving Scalar Product Protocol
Recently, privacy issues have become important in data analysis, especially when data is horizontally partitioned over several parties. In data mining, the data is typically represented as attribute-vectors and, for many applications; the scalar (dot) product is one of the fundamental operations that is repeatedly used. In privacy-preserving data mining, data is distributed across several parties. The efficiency of secure scalar products is important, not only because they can cause overhead in communication cost, but dot product operations also serve as one of the basic building blocks for many other secure protocols.