SDAP-K: A Kerberos-Assisted Secure Data Auditing Protocol for Cloud Storage
TL;DR
Experimental results indicate that the proposed framework offers a practical, lightweight, and reliable solution for secure cloud data auditing in enterprise cloud storage environments.
Abstract
Cloud storage services have become a fundamental component of modern computing infrastructures, enabling scalable and cost-effective data management. However, outsourcing data to remote cloud servers introduces significant security challenges, particularly in ensuring data integrity, secure access control, and efficient auditing of stored information. Existing cloud auditing schemes primarily focus on integrity verification and often rely on trusted third-party auditors, leading to additional trust assumptions, communication overhead, and metadata management complexity. To address these limitations, this research presents a Kerberos-Assisted Secure Data Auditing Protocol (SDAP-K) that integrates authenticated service exchange with lightweight integrity verification for outsourced cloud storage. The proposed framework employs Kerberos-based mutual authentication and ticket-driven access control to establish secure communication among the Data Owner, Authentication Server, Metadata Server, and Cloud Data Server. To verify storage correctness, an N-ary hash tree with the Modified Murmur hash algorithm is used to enable efficient file- and block-level auditing without requiring a trusted third-party auditor. The framework further incorporates metadata-assisted auditing, dynamic data operations, and an error localization and recovery mechanism that identifies and restores corrupted data blocks. Security analysis demonstrates that the proposed protocol mitigates unauthorized access, replay attacks, impersonation attempts, and malicious data modification. Experimental results indicate that SDAP-K reduces storage execution time by 18.6%, retrieval time by 24.3%, update time by 21.8%, file-level auditing overhead by 31.5%, and block-level auditing latency by 36.2% compared with state-of-the-art research, while eliminating the need for a trusted third-party auditor. The results indicate that the proposed framework offers a practical, lightweight, and reliable solution for secure cloud data auditing in enterprise cloud storage environments.