Certificateless data integrity auditing with sparse Merkle trees for the cloud-edge environment

Ensuring data integrity in cloud-edge environments is critical for IoT ecosystems but is challenged by dynamic data and resource constraints. This paper proposes a certificateless auditing scheme harmonizing cloud security with edge efficiency. By integrating online/offline cryptography and sparse Merkle trees, our approach achieves (1) significant user-side computation reduction via offline or edge-side tag generation, (2) [Formula: see text] dynamic update complexity versus traditional [Formula: see text] approaches, and (3) 75% communication overhead savings through pre-download mechanism. The scheme eliminates certificate management and mitigates Key Generation Centre (KGC) risks via decentralized trust mechanisms. Security proofs demonstrate resilience against KGC collusion and tag forgery under the Inv-CDH assumption. Experiments show our scheme audits faster than prior schemes, supporting 500k+ operations at sub-second latency. This work bridges scalability and real-time demands for smart cities and Industry 4.0 while enabling future extensions in ML-optimized caching and blockchain trust models.