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An Efficient Local-Recoding k-Anonymization Algorithm Based on Clusterin

  • Lifeng YuEmail author
  • Qiong Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8971)

Abstract

KACA is a typical local-recoding k-anonymization algorithm. It can generate k-anonymizing data with high quality. The main drawback of KACA algorithm is its high computational cost in dealing with large dataset. To remedy this problem, we propose an new efficient k-anonymization algorithm. The main idea of the proposed algorithm is that we first adopt the c-modes algorithm to partition the whole dataset into some large clusters, and then take KACA algorithm to k-anonymize each cluster separately. Finally, comprehensive experiments demonstrate the effectiveness of our algorithm.

Keywords

K-anonymity KACA algorithm C-modes algorithm Information loss 

Notes

Acknowledgements

This paper is supported by the major science and technology projects of Shaoxing city (2010A21034).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Computer BranchZhejiang Industry Polytechnic CollegeShaoxingChina

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