A Low-Overhead Auditing Protocol for Dynamic Cloud Storage Based on Algebra

Author:

Ding Fudong123ORCID,Wu Libing123ORCID,Zhang Zhuangzhuang123ORCID,Wu Xianfeng4,Ma Chao13ORCID,Liu Qin13

Affiliation:

1. School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China

2. Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Guangzhou 510000, China

3. Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, Wuhan 430072, China

4. Institute for Interdisciplinary Research, Jianghan University, Wuhan 430056, China

Abstract

With the widespread adoption of cloud storage, ensuring the integrity of outsourced data has become increasingly important. Various cloud storage auditing protocols based on public key cryptography have been proposed. However, all of them require complex cryptographic operations and incur significant storage and communication costs. To address the issues of significant storage overhead for data tags, high computational complexity of cryptographic algorithms, and limited efficiency of dynamic data algorithms in signature algorithm-based cloud storage outsourcing data integrity verification protocols, we propose a dynamic auditing protocol called AB-DPDP, which is based on algebra. Our protocol reduces the computational complexity of tag generation by utilizing basic algebraic operations instead of the traditional cryptographic method used in most current auditing protocols. To reduce storage overhead and protect private data, our protocol stores only tags, allowing for data to be restored through these tags, as opposed to storing both tags and data on the cloud server. To accommodate for more frequent and efficient data dynamics, we propose the dynamic index skip table data structure. Furthermore, the security of our proposed protocol is thoroughly proven based on the security definition of secure cloud storage. Finally, through theoretical analysis and experimental evaluation, we demonstrate the advantages of our scheme in terms of data privacy, storage overhead, communication overhead, computation overhead, and data dynamic efficiency.

Funder

National Basic Research Program of China

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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