Tools for privacy preserving Kernel methods in data mining

  • Authors:
  • Wan Haiping;He Huacan

  • Affiliations:
  • Intelligent Science Research Center, Beijing University of Telecommunication and Post, Beijing, China;Information Engineering Department, Northwest Polytechnical University, Xi'an, ShanXi, China

  • Venue:
  • AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
  • Year:
  • 2006

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Abstract

We provide an overview of the emerging issues in privacy preserving data mining. Also we develop solutions for two secure two-party computing problems. Many of the research issues focus on underlying blocks, we show how to integrate them with kernel methods in classifications. We evaluate their performance, privacy capacity, and draw some initial conclusions.