Title: Efficient public auditing for data migration across cloud systems

Authors: Haiyang Yu; Yongquan Cai; Fei Xue; Shanshan Kong; Gulzar Rana Khurram

Addresses: College of Computer Science, Beijing University of Technology, Beijing, China ' College of Computer Science, Beijing University of Technology, Beijing, China ' College of Information, Beijing Wuzi University, Beijing, China ' College of Computer Science, Beijing University of Technology, Beijing, China ' College of Computer Science, Beijing University of Technology, Beijing, China

Abstract: Cloud storage has gained great attention in recent years. It brings many benefits as well as security issues. Cloud auditing technology can ensure the integrity of cloud users' data. However, it lacks efficiency when dealing with the migration scenario of a large amount of cloud data. In this paper, we propose an efficient cloud auditing scheme which supports data migration auditing. We first construct a privacy-preserving auditing scheme that can audit cloud data during data migration, which can hugely reduce the migration cost when data corruption happens. We further extend the scheme to support data update during auditing. By supporting batch auditing for multiple cloud users' migration auditing tasks, our scheme could hugely improve the efficiency. Performance analysis demonstrates that our auditing scheme is secure and efficient.

Keywords: cloud auditing; data migration; batch auditing; audit efficiency; public auditing; cloud computing; cloud storage; privacy preservation; privacy protection; cloud security.

DOI: 10.1504/IJWMC.2017.083049

International Journal of Wireless and Mobile Computing, 2017 Vol.12 No.1, pp.41 - 48

Received: 30 Jul 2016
Accepted: 06 Dec 2016
Published online: 19 Mar 2017 *

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