Secure Multiparty Computation for Privacy Preserving Data Mining

Abstract

The increasing use of data-mining tools in both the public and private sectors raises concerns regarding the potentially sensitive nature of much of the data being mined. The utility to be gained from widespread data mining seems to come into direct conflict with an individual’s need and right to privacy. Privacy-preserving data-mining solutions achieve the somewhat paradoxical property of enabling a data-mining algorithm to use data without ever actually seeing it. Thus, the benefits of data mining can be enjoyed without compromising the privacy of concerned individuals.