A Method for Privacy Preserving Data Mining in Secure Multiparty Computation using Hadamard Matrix

Secure multiparty computation allows multiple parties to participate in a computation. SMC (secure multiparty computation) assumes n parties where n>1. All the parties jointly compute a function. Privacy preserving data mining has become an emerging field in the secure multiparty computation. Privacy preserving data mining preserves the privacy of individual's data. Privacy preserving data mining outputs have the property that the only information learned by the different parties is only the output of the algorithm. In this paper, we use a mathematical function hadamard matrix. All the computation multiplied by the hadamard matrix. Using this, security and privacy of the individual’s data increased. Thus, we can say that this protocol fulfill the requirement of privacy and security.