Privacy Preserving Clustering Based on Fuzzy Data Transformation Methods

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Security
Format: PDF
Knowledge extraction process poses certain problems like accessing sensitive, personal or business information. Privacy invasion occurs owing to the abuse of personal information. Hence privacy issues are challenging concern of the data miners. Privacy preservation is a complex task as it ensures the privacy of individuals without losing the accuracy of data mining results. In this paper, fuzzy based data transformation methods are proposed for privacy preserving clustering in centralized database environment. In case one, a fuzzy data transformation method is proposed and various experiments are conducted by varying the fuzzy membership functions such as Z-shaped fuzzy membership function, Triangular fuzzy membership function, Gaussian fuzzy membership function to transform the original dataset.

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