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Progress in Anonymous Privacy-Preserving in Data Mining |
TAN Ying |
Department of Information, Yunnan University of Finance and Economics, Kunming 650221, China |
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Abstract: With the development of information technology, an important issue is to ensure the high usability of the data and to protect the privacy. The privacy-preserving technology is related with the data encryption, the data distortion and the data anonymity in data mining. Among them, the most primary technology is the anonymous privacy-preserving technology. In that respect, a various privacy preserving models were proposed This paper focuses on the k-anonymous model, the l-diversity model, the (α, K)-anonymous model and the t-closeness model, and it is pointed out that each anonymous model has its, advantages and disadvantages. The commonly used anonymity technology and the major anonymous quality measurement methods are reviewed. In the future, the anonymity technology will face new problems, and the privacy-preserving will be further considered in data mining.
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Received: 10 May 2012
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