An Efficient and Scalable Auditing Scheme for Cloud Data Storage using an Enhanced B-tree
Tariqul Islam, Faisal Haque Bappy, Md Nafis Ul Haque Shifat, Farhan Ahmad, Kamrul Hasan, Tarannum Shaila Zaman
TL;DR
The paper tackles dynamic data integrity auditing in cloud storage by replacing traditional static or blockchain-based approaches with an Enhanced B-tree (EB-tree) that supports insert, update, and delete operations in a centralized setting. It introduces a leaf-block-centric EB-tree that stores data blocks with no explicit keys and uses per-subtree block counts to locate and modify blocks, achieving balanced growth and efficient dynamic auditing. Security is reinforced through cryptographic hashes and a private seed used during hashing to prevent tampering, while auditing leverages a sibling-path root-hash verification. Experimental results show EB-tree outperforms Merkle-tree based and blockchain-based auditing in block modifications, retrieval, and batch auditing times, demonstrating practical scalability and privacy-preserving integrity verification for cloud data.
Abstract
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.