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Privacy-Preserving Decision Trees over Vertically Partitioned Data

  • Jaideep Vaidya
  • Chris Clifton
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3654)

Abstract

Privacy and security concerns can prevent sharing of data, derailing data mining projects.Distributed knowledge discovery, if done correctly, can alleviate this problem. In this paper, we tackle the problem of classification. We introduce a generalized privacy preserving variant of the ID3 algorithm for vertically partitioned data distributed over two or more parties. Along with the algorithm, we give a complete proof of security that gives a tight bound on the information revealed.

Keywords

Leaf Node Information Gain Association Rule Mining Class Attribute Class Site 
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

© IFIP International Federation for Information Processing 2005

Authors and Affiliations

  • Jaideep Vaidya
    • 1
  • Chris Clifton
    • 2
  1. 1.MSIS DepartmentRutgers UniversityNewarkUSA
  2. 2.Department of Computer SciencePurdue UniversityWest LafayetteUSA

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