Certificateless data integrity auditing with sparse Merkle trees for the cloud-edge environment
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a certificateless auditing scheme for cloud-edge IoT, reducing computation and communication overhead. It enhances data integrity and security without certificate management, improving efficiency for smart cities.
Area Of Science
- Cybersecurity
- Cloud Computing
- Internet of Things (IoT)
Background
- Data integrity in cloud-edge IoT is crucial but hindered by dynamic data and resource limits.
- Existing solutions often face challenges with scalability and efficiency in dynamic environments.
Purpose Of The Study
- To propose a novel certificateless auditing scheme for cloud-edge environments.
- To enhance data integrity while harmonizing cloud security with edge efficiency.
Main Methods
- Integration of online/offline cryptography and sparse Merkle trees.
- Development of a certificateless auditing scheme with decentralized trust mechanisms.
- Utilizing pre-download mechanisms for communication overhead reduction.
Main Results
- Significant reduction in user-side computation through offline/edge-side tag generation.
- [Formula: see text] dynamic update complexity compared to traditional [Formula: see text] methods.
- Achieved 75% communication overhead savings.
- Demonstrated resilience against Key Generation Centre (KGC) collusion and tag forgery.
- Faster audit times with sub-second latency for over 500k operations.
Conclusions
- The proposed scheme effectively addresses data integrity challenges in cloud-edge IoT ecosystems.
- It offers improved scalability and real-time performance for applications like smart cities and Industry 4.0.
- The framework supports future extensions in machine learning-optimized caching and blockchain trust models.
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