Privacy-Preserving Classification on Horizontally Partitioned Data

With the appearance of large-scale database and people's increasing concern about individual privacy, privacy-preserving data mining becomes a hot study area, to which the support vector machine(SVM) belongs. In this paper, a novel privacy-preserving SVM for horizontally partitioned data is given. It has comparable accuracy to that of an ordinary SVM as we obtain the SVM by using the distinct property of the orthogonal matrices.