Data mining is the process of extracting hidden information from the database. Data mining is emerging as one of the key features of many business organizations. The current trend in business collaboration shares the data and mined results to gain mutual benefit. The problem of privacy-preserving data mining has become more important in recent years because of the increasing ability to store personal data about users, and the increasing sophistication of data mining algorithms to leverage this information. Apart from classification and regression, one of the most important tasks of data mining is to find patterns in data. In particular, new advances in data mining and knowledge discovery that allow for the extraction of hidden knowledge in enormous amount of data impose new threats on the seamless integration of information. In this paper, we consider the problem of building privacy preserving algorithms for one category of data mining techniques, the association rule mining.
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