Genuine and secure public auditing for the outsourced data in cloud
by Jianhong Zhang; Hongxin Meng
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 14, No. 2, 2019

Abstract: In cloud storage, the most common concerns for users are data integrity, confidentiality and availability. Recently, many data integrity auditing schemes have been proposed, some of which achieved privacy-preserving public auditing, some of which realised data sharing and group dynamic, and some of which supported data dynamic. However, as far as we know, there does not exist a practical auditing scheme which can simultaneously realise all the functions mentioned above; In addition, all the existing schemes adopt the method of computing message authentication code (MAC) by users to achieve the following data integrity auditing, nevertheless, it is a arduous task to compute MACs for these cloud users with constrained computing and storage capabilities. In this paper, we propose a novel privacy-preserving public auditing scheme for shared data in the cloud, which can also support data dynamic operation and group dynamic. First, we bring proxy signature into the existing auditing scheme. The cloud user can delegate the computation of MACs to a cloud computing server, so that the user's burden would be greatly reduced; second, by introducing a Lagrange interpolating polynomial, our scheme realises the identity privacy-preserving in the precondition of almost no addition of any new computation and less storage space, moreover it makes group dynamic simple; third, we make an index-switch table and combine it with the Merkle hash tree to realise the practical and secure dynamic operations of shared data by group users; fourth, in our scheme, the cloud storage server will add its private key in producing the proof information to protect the data privacy and resist the active attack. Theoretical analysis demonstrates our scheme is provably secure.

Online publication date: Tue, 30-Jul-2019

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