An Efficient and Scalable Auditing Scheme for Cloud Data Storage Using an Enhanced B-Tree

An efficient, scalable, and provably secure dynamic auditing scheme is highly desirable in the cloud storage environment for verifying the integrity of the outsourced data. Most of the existing work on remote integrity checking focuses on static archival data and therefore cannot be applied to cases where dynamic data updates are more common. Additionally, existing auditing schemes suffer from performance bottlenecks and scalability issues. To address these issues, in this paper, we present a novel dynamic auditing scheme for centralized cloud environments leveraging an enhanced version of the B-tree. Our proposed scheme achieves the immutable characteristic of a decentralized system (i.e., blockchain technology) while effectively addressing the synchronization and performance challenges of such systems. Unlike other static auditing schemes, our scheme supports dynamic insert, update, and delete operations. Also, by leveraging an enhanced B-tree, our scheme maintains a balanced tree after any alteration to a certain file, improving performance significantly. Experimental results show that our scheme outperforms both traditional Merkle Hash Tree-based centralized auditing and decentralized blockchain-based auditing schemes in terms of block modifications (e.g., insert, delete, update), block retrieval, and data verification time.