Privacy Preserving Data Mining: A Novel Approach to Secure Sensitive Data Based on Association Rules
Syed Shujauddin Sameer
Syed Shujauddin Sameer, Department of Computer Science, King Khalid University, Abha, Saudi Arabia.
Manuscript received on March 30, 2014. | Revised Manuscript received on April 14, 2014. | Manuscript published on April 30, 2014. | PP: 392-395 | Volume-3, Issue-4, April 2014. | Retrieval Number: D3038043414/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The availability of data on the internet is increasing on a larger basis daily .Privacy Preservation data mining has emerged to address one of the side effects of data mining Technology. The threat to individual privacy through data mining is able to infer sensitive information from Non-sensitive information or unclassified data. There is a n urgent need to be able to infer some mechanism to avoid the projection of all the sensitive information .An approach in data mining techniques is very much essential. Alteration of data, filtering of the data, blocking of the data are Some of the approaches. Given specific rules to be hidden, the techniques involve is to hide only the given sensitive data. In this work we assume that only sensitive datais given and we analyze the approaches to secure sensitive data in the database.
Keywords: Privacy preserving data mining, Association rules, Sensitive data.