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Data Distortion for Privacy Protection in a Terrorist Analysis System

  • Shuting Xu
  • Jun Zhang
  • Dianwei Han
  • Jie Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3495)

Abstract

Data distortion is a critical component to preserve privacy in security-related data mining applications, such as in data mining-based terrorist analysis systems. We propose a sparsified Singular Value Decomposition (SVD) method for data distortion. We also put forth a few metrics to measure the difference between the distorted dataset and the original dataset. Our experimental results using synthetic and real world datasets show that the sparsified SVD method works well in preserving privacy as well as maintaining utility of the datasets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shuting Xu
    • 1
  • Jun Zhang
    • 1
  • Dianwei Han
    • 1
  • Jie Wang
    • 1
  1. 1.Department of Computer ScienceUniversity of KentuckyLexingtonUSA

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