AbstractsComputer Science

Development of Transformationbased Privacy Preservation Methods For Data Mining;

by Poovammal.E

Institution: SRM University
Year: 2014
Record ID: 1184020
Full text PDF: http://shodhganga.inflibnet.ac.in/handle/10603/17841


newline Data-mining is a task of discovering significant/salient newlinepatterns/rules/results from a set of large amount of data stored in databases, newlinedata warehouses or in other information repositories. Eventhough the focus on newlinedata-mining technology has been on the discovery of general patterns (not on newlineany specific information regarding individuals) some data-mining applications newlinemay require access to individual s records having sensitive privacy data. Data newlinecontaining structured information on individuals is referred to as micro-data. newlineAbundance of recorded, personal information available in electronic form newlinecoupled with increasingly powerful data-mining tools, poses a threat to newlineprivacy and data security. The prime objective of this research is to find a newlinesolution to this problem. newlineEventhough, the identifying attributes are not published, some set newlineof attributes in a released table (called quasi identifiers) may be linked with newlineexternal data base leaking the sensitive data. To alleviate this problem, the so newlinecalled K-anonymity and L-diversity principles and their improved versions newlinehave been used popularly in the earlier research works. But, all such methods newlinesuffer from proximity and divergence breach considerations%%%