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SIV: a structural integrity verification approach of cloud components with enhanced privacy

机译:SIV:具有增强的隐私性的云组件的结构完整性验证方法

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摘要

Private data leakage is a threat to current integrity verification schemes of cloud components. To address this issue, this work proposes a privacy-enhancing Structural Integrity Verification (SIV) approach. It is made up of three processes: proof organization, proof transformation, and integrity judgement. By introducing a Merkle tree technique, the integrity of a constituent part of a cloud component on a node is represented by a root value. The value is then masked to cipher texts in proof transformation. With the masked proofs, a structural feature is extracted and validated in an integrity judgement by a third-party verification provider. The integrity of the cloud component is visually displayed in the output result matrix. If there are abnormities, the corrupted constituent parts can be located. Integrity is verified through the encrypted masked proofs. All raw proofs containing sensitive information stay on their original nodes, thus minimizing the attack surface of the proof data, and eliminating the risk of leaking private data at the source. Although some computations are added, the experimental results show that the time overhead is within acceptable bounds.
机译:私有数据泄漏是对当前云组件完整性验证方案的威胁。为了解决此问题,这项工作提出了一种增强隐私的结构完整性验证(SIV)方法。它由三个过程组成:证明组织,证明转换和完整性判断。通过引入Merkle树技术,节点上云组件的组成部分的完整性由根值表示。然后将该值屏蔽以在证明变换中对文本进行密文处理。使用掩盖的证据,可以由第三方验证提供程序在完整性判断中提取并验证结构特征。云组件的完整性以可视方式显示在输出结果矩阵中。如果存在异常,则可以找到损坏的组成部分。完整性通过加密的屏蔽证明进行验证。所有包含敏感信息的原始证明都保留在其原始节点上,从而最大程度地减少了证明数据的攻击面,并消除了在源头泄漏私人数据的风险。尽管添加了一些计算,但实验结果表明时间开销在可接受的范围内。

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