【摘 要】
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There are privacy leakage risks and degradation of performance when verifying the integrity of components with existing methods in a cloud.To address the issue,this work proposes a structural integrit
【机 构】
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Key Laboratory of Aerospace Information Security and Trusted Computing,Ministry of Education,School
【出 处】
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第十二届中国可信计算与信息安全学术会议
论文部分内容阅读
There are privacy leakage risks and degradation of performance when verifying the integrity of components with existing methods in a cloud.To address the issue,this work proposes a structural integrity verification approach,named SIV,to enhance the privacy and performance.It includes 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 in proof organization.Then the Merkle root value is masked in proof transformation.The first two processes are executed inside the cloud,ensuring all raw proofs are processed on their born nodes and never go nowhere.In this way the attack surfaces to proofs could be minimized,and the privacy leakage risks are eliminated from the source.With all masked proofs from the cloud,a structural feature is extracted and validated in integrity judgement on TPV.A verification result will be given after the validation.In the three processes there are some computations added,but there are a great reduction of proof data size,which could balance the performance.The experimental results on three datasets show that the proposed approach is effective in raising integral proofs or locating compromised constituent parts of a cloud component.In the meantime the time overhead is within an acceptable range.
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