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

Abstract

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.