Cloud data integrity checking protocol from lattice. (2015)

• Record Type: Journal Article
• Authors: Zhao, Xiufeng; Wang, Xiang; Xu, Hao; Wang, Yilei
• Is Part Of: International journal of high performance computing and networking. Volume 8:Number 2(2015)
• Page Start: 167
• Page End: 175
• Publication Date: 2015
• Subjects: cloud storage -- cloud data integrity -- data integrity checking -- privacy preservation -- privacy protection -- homomorphic linear authentication -- lattice based homomorphic signatures -- cloud computing -- cloud security -- quantum computing -- quantum attacks -- blind checking -- third party auditing -- TPA -- known-proof forgery attacks; High performance computing -- Periodicals; Computer networks -- Periodicals; High performance computing; Periodicals; 004.05
• Languages: English
• ISSNs: 1740-0562

Abstract

Cloud computing is a distributed computing model, which provides services and resources. As a new type of storage services, cloud storage provides a new method for mass data storage management. Nowadays, more and more users upload their data to cloud storage servers and retrieve data when needed. One of the basic tasks of cloud storage is to guarantee the integrity between retrieved and uploaded data. Therefore, data integrity checking of cloud storage becomes a key issue. This paper proposes a privacy-preserving public verifying cloud data integrity checking protocol. To achieve security against quantum computer attacks, we resort to constructing homomorphic linear authenticator based on a lattice-based homomorphic signature algorithm. To eliminate data content exposure to achieve privacy, we use the blind checking technique. Theoretical analysis indicates that our scheme achieves security against malicious cloud server and privacy against third party auditor (TPA), and resists the known-proof forgery attack. Compared with other protocols, our protocol does not resort to rank-based authenticated skip list, saving storage and communication overhead. Furthermore, it makes use of matrix-vector multiplication operation, avoiding great amount of module exponential operation, which reduces the computational labour for cloud server and TPA.