An Experimental Analysis on Information Hiding using Data Mining
Author Name : Naveen Kumari, Tarun Dalal
Sometimes companies involved in the similar business are often willing to cooperate each other so that they can perform data mining to extract knowledge from combined datasets. Generally the main objective behind such kind of data mining is mutual gain of all involved parties. But the company dataset contains private or sensitive data. Therefore companies may want certain strategic or private data called sensitive patterns not to be published in the database. Therefore, before the database is released for sharing, some sensitive patterns have to be hidden in the database because of privacy or security concerns. To solve this problem, sensitive-knowledge-hiding (association rules hiding) problem has been discussed in the research community working on security and knowledge discovery. The aim of these algorithms is to extract as much as non sensitive knowledge from the collaborative databases as possible while protecting sensitive information.
In this paper, an efficient algorithm using data mining approach to protect sensitive information has been designed and proved.