Proceedings of the
The Nineteenth International Conference on Computational Intelligence and Security (CIS 2023)
December 1 – 4, 2023, Haikou, China
S-Auditor: an Efficient Data Auditing Solution for Ensuring Integrity and Semantic Correctness
1College of Computer, Qinghai Normal University, China /EADDRESS/2Digital Finance Department, Bank of Qinghai, China.
3School of Mathematics and Statistics, Qinghai Normal University, China.
ABSTRACT
As the volume of user data continues to surge, more users are opting to store their data in the cloud. However, the cloud faces the persistent risk of data corruption stemming from equipment failures, hacker attacks. Furthermore, when a user carries out file operations like uploading, modifying, and deleting data, the semantics integrity of the data can be compromised. How to ensure both data integrity and semantic correctness has become a crucial issue that needs to be addressed. Existing data auditing algorithms require auditors to access all the cloud data, resulting in substantial bandwidth costs. The emerging provable data possession (PDP) scheme offers more efficient alternatives by enabling auditors to conduct audits without holding the data. However, current PDP schemes primarily focus on auditing data integrity and do not encompass verification of semantics correctness. We introduce a pioneering secure data auditor called S-Auditor, the first of its kind with the capability to simultaneously verify both data integrity and semantic correctness. S-Auditor also supports public auditing, allowing anyone with access to public information to conduct data audits. This feature makes S-Auditor highly adaptable to open data environments, such as the cloud. We conduct a thorough analysis of S-Auditor's correctness and security, with the evaluation results demonstrating its superior execution efficiency.
Keywords: Provable data possession, Public auditing, Cloud storage, Data integrity, Semantic correctness.
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1College of Computer, Qinghai Normal University, China /EADDRESS/2Digital Finance Department, Bank of Qinghai, China.
3School of Mathematics and Statistics, Qinghai Normal University, China.
ABSTRACT
As the volume of user data continues to surge, more users are opting to store their data in the cloud. However, the cloud faces the persistent risk of data corruption stemming from equipment failures, hacker attacks. Furthermore, when a user carries out file operations like uploading, modifying, and deleting data, the semantics integrity of the data can be compromised. How to ensure both data integrity and semantic correctness has become a crucial issue that needs to be addressed. Existing data auditing algorithms require auditors to access all the cloud data, resulting in substantial bandwidth costs. The emerging provable data possession (PDP) scheme offers more efficient alternatives by enabling auditors to conduct audits without holding the data. However, current PDP schemes primarily focus on auditing data integrity and do not encompass verification of semantics correctness. We introduce a pioneering secure data auditor called S-Auditor, the first of its kind with the capability to simultaneously verify both data integrity and semantic correctness. S-Auditor also supports public auditing, allowing anyone with access to public information to conduct data audits. This feature makes S-Auditor highly adaptable to open data environments, such as the cloud. We conduct a thorough analysis of S-Auditor's correctness and security, with the evaluation results demonstrating its superior execution efficiency.
Keywords: Provable data possession, Public auditing, Cloud storage, Data integrity, Semantic correctness.
Download PDF