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SM2-Based Offline/Online Efficient Data Integrity Verification Scheme for Multiple Application Scenarios
Xiuguang Li1,2, Zhengge Yi3, Ruifeng Li2
1State Key Laboratory of Integrated Service Networks, Xidian University, Xi'an 710126, China.
Sensors (Basel, Switzerland)
|May 13, 2023
Summary
This study introduces an efficient data integrity verification scheme for cloud storage, particularly for Internet of Things and medical big data. The new scheme ensures data security and privacy while reducing user computational load.
Area of Science:
- Computer Science
- Information Security
- Cloud Computing
Background:
- Cloud storage and computing offer convenience but necessitate robust data integrity verification.
- Existing schemes are inadequate for the unique demands of Internet of Things (IoT) and medical big data environments.
- Enhanced data integrity verification is crucial for big data storage and security.
Purpose of the Study:
- To design an efficient data integrity verification scheme tailored for IoT and medical big data storage.
- To address the limitations of current schemes in complex big data environments.
- To enhance data security and privacy in cloud-based big data applications.
Main Methods:
- Developed an SM2-based offline/online data integrity verification scheme.
- Utilized the SM4 block cryptography algorithm for data privacy protection.
- Implemented a dynamic hash table for efficient data updates and management.
Main Results:
- The proposed scheme provides secure and efficient data integrity verification.
- It enables offline tag generation and batch audits, reducing user computational burden.
- The scheme is proven safe and efficient through rigorous security analysis.
Conclusions:
- The novel SM2-based scheme effectively meets the integrity verification needs of IoT and medical big data.
- It offers a practical solution for enhancing data security and privacy in cloud environments.
- The scheme's efficiency and security make it suitable for diverse application scenarios.
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