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Privacy Preserving Data Mining: A New Methodology for Data Transformation

  • A. K. Upadhayay
  • Abhijat Agarwal
  • Rachita Masand
  • Rajeev Gupta

Abstract

Today, privacy preservation is one of the greater concerns in data mining. While the research to develop different techniques for data preservation is on, a concrete solution is awaited. We address the privacy issue in data mining by a novel privacy preserving data mining technique. We develop and introduce a novel ICT (inverse cosine based transformation) method to preserve the data before subjecting it to clustering or any kind of analysis. A novel ‘privacy preserved k-clustering algorithm’ (PrivClust) is developed by embedding our ICT method into existing K-means clustering algorithm. This algorithm is explicitly designed with conversion to a privacy-preserving version in mind. The challenge was how to meet privacy requirements and guarantee valid clustering results as well. Simulation was carried out using Matlab. Our analysis and simulation show that this algorithm efficiently preserves the intended information on the one hand and yields valid cluster results on the other.

Keywords

Data Mining Privacy Preservation National Basketball Association Secure Multiparty Computation Privacy Preserve Data Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Indian Institute of Information Technology, India 2009

Authors and Affiliations

  • A. K. Upadhayay
    • 1
  • Abhijat Agarwal
    • 1
  • Rachita Masand
    • 1
  • Rajeev Gupta
    • 2
  1. 1.Amity School of Engineering and TechnologyNoida, U.P.India
  2. 2.Rajasthan Technical UniversityKota, RajasthanIndia

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