A Review of Privacy Preserving in Document Clustering

Association Rule Mining from a large amount of data is one of the most important issues in data mining, because the discovered knowledge is commercially valuable. Sometimes companies involved in the similar business are often willing to co-operate 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 Therefore companies may want certain strategic or private data called sensitive patterns not to be published in the database.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. , a lot of research has been completed to solve the problem. In this thesis, we will introduce an efficient algorithm to protect sensitive information.