Nearest neighbor tour circuit encryption algorithm based random Isomap reduction

Abstract

This paper presents nearest neighbor tour circuit encryption algorithm based random Isomap reduction. In order to be suited for privacy-preserving classification, we first alter the selection fashion of the parameters nearest neighbor number k and embedded space dimension d of Isomap reduction algorithm. Further we embed the tourists' sensitive attribution into random dimension space using random Isomap reduction, thus the sensitive attributes are encrypted and protected. Because the transformed space dimension d and nearest neighbor number k are both random, this algorithm is not easily be breached. In addition, Isomap can keep geodesic distance of two points of dataset, so the precision change of classification after encryption can be controlled in a small scope . The experiment show that if we select appropriate parameters, then nearest neighbors of every point may be completely consistent. The present algorithm can guarantee that the security and the precision both achieve the requirements. © 2009 Springer.