4.6 Article

On the Soundness and Security of Privacy-Preserving SVM for Outsourcing Data Classification

期刊

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TDSC.2017.2682244

关键词

Privacy-preserving; classification; SVM; paillier encryption

资金

  1. Natural Science Foundation of China [61602240]
  2. Natural Science Foundation of Jiangsu Province of China [BK20150760]
  3. Research Fund of Guangxi Key Laboratory of Trusted Software [kx201611]

向作者/读者索取更多资源

Recently, Rahulamathavan et al. propose a privacy preserving scheme for outsourcing SVM classification. Their core contribution is a secure protocol to attain the sign of numbers in encrypted form. In this paper, we observe that Rahulamathavan et al.'s protocol will suffer from some soundness and security problems. Then, we propose a new scheme to securely obtain the encrypted numbers' sign. Theoretical analysis and experiment results show our proposed scheme can not only fix the soundness and security problems, but also achieve higher efficiency.

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