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A Data Perturbation Method by Field Rotation and Binning by Averages Strategy for Privacy Preservation

  • Mohammad Ali Kadampur
  • Somayajulu D.V.L.N.
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5326)

Abstract

In this paper a novel technique useful to guarantee privacy of sensitive data with specific focus on numeric databases is presented. It is noticed that analysts and decision makers are interested in summary values of the data rather than the actual values. The proposed method considers that the maximum information lies in association of attributes rather than their actual proper values. Therefore it is aimed to perturb attribute associations in a controlled way, by shifting the data values of specific columns by rotating fields. The number of rotations is determined via using a support function for association rule handling and an algorithm that computes the best-choice rotation dynamically. Final summary statistics such as average, standard deviation of the numeric data are preserved by making bin average replacements for the actual values. The methods are tested on selected datasets and results are reported.

Keywords

Association Rule Minimum Support Association Rule Mining Average Strategy Privacy Preservation 
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

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Mohammad Ali Kadampur
    • 1
  • Somayajulu D.V.L.N.
    • 1
  1. 1.Department of Computer Science and EngineeringNational Institute of TechnologyWarangalIndia

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