Work

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

Year: 2025
Type: article
Abstract: 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.
Institution: Hebei University
Language: English
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4416089168
FWCI: 3.321
Cites: 21
Cited by: 3
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