Blockchain-Based Multi-Level Data Secure Audit with Hierarchical Key Derivation

作者：Xuan Chen, Lei Zhou, Chunfei Pan, Zhen-Zhu Chen, Xiao Yang, Chenlu Zhuansun · 发表于：2025 IEEE 5th International Conference on Applied Mathematics, Modeling and Computer Simulation (AMMCS) · 年份：2025 · DOI：10.1109/ammcs65761.2025.11459873

Cloud storage has emerged as a critical infrastructure for modern data sharing, yet persistent security challenges remain in ensuring data integrity. Current solutions are constrained by several fundamental limitations: performance and scalability bottlenecks inherent to centralized key generation architectures, storage inefficiencies resulting from unoptimized integrity tags, and unavoidable reliance on trusted third-party auditors. To address these challenges, we propose a blockchain-based multi-level secure data audit scheme with hierarchical key derivation that introduces three key innovations. First, our hierarchical key derivation framework with key iteration eliminates centralized bottlenecks while enabling efficient large-scale key distribution across partitioned environments. Second, we introduce adaptive tag optimization strategies including: random dynamic signatures for high-security data, Merkle-tree based tag aggregation for medium-security data (reducing storage overhead), and hash-based deduplication for low-security content, resulting in lowering storage costs and improving audit efficiency. Third, we present automated integrity auditing through blockchain smart contracts, completely removing third-party dependencies. Comprehensive security analysis and experimental results demonstrate that our proposal achieves both security guarantees and operational efficiency.