Dynamic Outsourced Data Audit Scheme for Merkle Hash Grid-Based Fog Storage With Privacy-Preserving

Abstract

The security of fog computing has been researched and concerned with its development, where malicious attacks pose a greater threat to distributed data storage based on fog computing. Also, the rapid increasing on the number of terminal devices has raised the importance of fog computing-based distributed data storage. In response to this demand, it is essential to establish a secure and privacy-preserving distributed data auditing method that enables security protection of stored data and effective control over identities of auditors. In this paper, we propose a dynamic outsourced data audit scheme for Merkle hash grid-based fog storage with privacy-preserving, where fog servers are used to undertake partial outsourced computation and data storage. Our scheme can provide the function of privacy-preserving for outsourced data by blinding original stored data, and supports data owners to define their auditing access policies by the linear secret-sharing scheme to control the identities of auditors. Further, the construction of Merkle hash grid is used to improve the efficiency of dynamic data operations. Also, a server locating approach is proposed to enable the third-part auditor to identify specific malicious data fog servers within distributed data storage. Under the proposed security model, the security of our scheme can be proved, which can further provide collusion resistance and privacy-preserving for outsourced data. Additionally, both theoretical and experimental evaluations illustrate the efficiency of our proposed scheme.