A Secure Protocol to Maintain Data Privacy in Data Mining

Recently, privacy issues have becomes important in data mining, especially when data is horizontally or vertically partitioned. For the vertically partitioned case, many data mining problems call be reduced to securely computing the scalar product. Among these problems, we call mention association rule mining over vertically partitioned data. Efficiency of a secure scalar product call be measured by the overhead of communication needed to ensure this security. Several solutions have been proposed for privacy preserving association rule mining in vertically partitioned data. But the main drawback of these solutions is the excessive overhead communication needed for ensuring data privacy. Ill this paper we propose a new secure scalar product with the aim to reduce the overhead communication.