Privacy preserving for data mining applications

Abstract EN

The results of data Mining (DM) such as association rules, classes, clusters, etc, will be readily available for working team.

So the mining will penetrate the privacy of sensitive data and makes the stolen of the knowledge resulted much more easily.

The main objective of the proposed system is preserving the privacy of data mining, that will done by developing algorithms for modifying, encrypting and distributing the original data in the database to be mined.

So we ensure the privacy of data (original data in database that will be mined) and the privacy of knowledge (the association rules extracted from mined database) even after the mining process has taken place.

The problem that arises when confidential information can be derived from released data by unauthorized users can be solved.