IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Limiting disclosure of sensitive data in sequential releases of databases
Information Sciences: an International Journal
Trends and research directions for privacy preserving approaches on the cloud
Proceedings of the 6th ACM India Computing Convention
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Privacy preserving becomes an important issue in the development progress of data mining techniques. Privacy preserving data mining has become increasingly popular because it allows sharing of privacy-sensitive data for analysis purposes. So people have become increasingly unwilling to share their data, frequently resulting in individuals either refusing to share their data or providing incorrect data. In turn, such problems in data collection can affect the success of data mining, which relies on sufficient amounts of accurate data in order to produce meaningful results. In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed for privacy preserving data mining of multidimensional data records. This paper intends to reiterate several privacy preserving data mining technologies clearly and then proceeds to analyze the merits and shortcomings of these technologies.