Categorization and Assessment of Approaches of PPDDM Based on Techniques of Privacy Preserving

One of the fresh aspects in data mining study is to develop techniques relating to the obsessions of privacy preserving, particularly, relating to the fact that techniques of data mining could be able to create sound models when the precise information of data is inaccessible. As a result of this research, numbers of data mining techniques with respect to privacy preserving are introduced in this study. One of these techniques - suggested in this paper - are to utilize methods of cryptography in data mining with respect to privacy preserving in distributed databases. We assume that data are stored in some private participants, and these participants agree upon a specific sort of estimating of data mining where the private characteristic of arrivals is preserved, and only the result of data mining is to be revealed. Variety of techniques has already been introduced in this field. This paper is to analyze and assess techniques of privacy preserving, introducing a framework based on methods of cryptography in data mining with respect to the privacy preserving. Considering the prevailing application of data mining methods in distributed databases, the suggested classification can possibly be influential in opting for a proper approach.

Categorization and Assessment of Approaches of PPDDM Based on Techniques of Privacy Preserving Keywords:

Cryptography , Distributed Data Mining , Privacy Preserving