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海南大学,海南 海口 570228
Received:26 November 2025,
Revised:2026-01-22,
Accepted:26 January 2026,
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Peng Su, Feng Li, Yin Yiran. Remote Data Integrity Checking with Ownership Transfer Based on Trusted Execution Environment[J/OL]. Telecommunications Science, 2026.
Peng Su, Feng Li, Yin Yiran. Remote Data Integrity Checking with Ownership Transfer Based on Trusted Execution Environment[J/OL]. Telecommunications Science, 2026. DOI: 10.11959/j.issn.1000-0801.033.
云存储的普及与数据所有权转移需求的增长,使得支持所有权转移的远程数据完整性验证成为保障云数据安全的关键技术。然而,现有方案普遍存在数据所有者计算负担重、依赖不可信第三方审计者、通信开销大以及缺乏有效的不可否认性机制等问题。为解决上述挑战,提出了一种基于可信执行环境的支持所有权转移的远程数据完整性验证方案。该方案将完整性验证与所有权转移过程中的所有关键计算任务安全地卸载至云服务提供商平台的TEE内执行。基于除TEE的隔离保护外所有实体均不可信的强威胁模型进行了形式化安全分析,并利用Intel SGX开发了原型系统,通过与多种代表性方案进行对比实验以评估其性能。实验结果表明,该方案在标签生成等阶段的计算效率优于对比的方案,计算开销降低幅度在10.1%至86.4%之间,同时实现了云服务提供商与验证者之间的零通信开销。
The popularization of cloud storage and the growing demand for data ownership transfer have made remote data integrity verification with ownership transfer a key technology for safeguarding cloud data security. However
existing schemes were generally plagued by problems such as heavy computational burden on data owners
reliance on untrusted third-party auditors
high communication overhead
and lack of effective non-repudiation mechanisms. To address these challenges
a remote data integrity verification scheme with ownership transfer based on Trusted Execution Environment (TEE) is proposed in this paper. All critical computational tasks in the integrity verification and ownership transfer are securely offloaded to the TEE of the cloud service provider’s platform by our scheme. Formal security analysis is conducted based on a strong threat model where all entities except the isolation protection of TEE are untrusted
and a prototype system is developed using Intel SGX. Comparative experiments with various representative schemes are performed to evaluate its performance. The experimental results demonstrate that this scheme achieves superior computational efficiency in stages such as HVT (Homomorphic Verifiable Tag) generation compared to the benchmark schemes
with computational overhead reductions ranging from 10.1% to 86.4%. Additionally
it achieves zero communication overhead between cloud service providers and verifiers.
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