Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing

TLDR

Cloud computing enables remote data storage, but the loss of physical possession makes ensuring data integrity difficult, making public auditability essential. The study aims to establish a third‑party auditor that can efficiently verify cloud data without requiring a local copy and without compromising user privacy. This is achieved by combining a public‑key homomorphic authenticator with random masking, and extending it with bilinear aggregate signatures to support simultaneous audits for multiple users. Security and performance analyses demonstrate that the proposed schemes are provably secure and highly efficient.

Abstract

Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in Cloud Computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. Thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) The third party auditing process should bring in no new vulnerabilities towards user data privacy. In this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient.