Authors: Xu Dong Zhu; Hui Li; Feng Hua Li
Addresses: School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an, Shaanxi 710055, China ' School of Telecommunication Engineering, Xidian University, Xi'an, Shaanxi 710071, China ' State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
Abstract: Cloud computing enables customers with limited computational resources an economically promising paradigm of computation outsourcing. However, how to protect customers' confidential data that is processed and generated during the computation is becoming a major security concern. To mitigate this problem, in this paper, we present a secure outsourcing mechanism for training and evaluating large-scale logistic regression classifier in cloud. Our mechanism enables a customer to securely harness the cloud, while keeping both the sensitive input and output of the computation private. Thorough security analysis and prototype experiments on Amazon EC2 demonstrate the validity and practicality of our proposed design.
Keywords: cloud computing; computation outsourcing; logistic regression; privacy preservation; privacy protection; cloud security.
International Journal of Grid and Utility Computing, 2013 Vol.4 No.2/3, pp.144 - 150
Received: 24 Aug 2012
Accepted: 23 Sep 2012
Published online: 18 Sep 2014 *