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Watchword-oriented and time-stamped algorithms for tamper-proof cloud provenance cognition

机译:面向应用词和时间戳的算法,可防止篡改云源

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Provenance is derivative journal information about the origin and activities of system data and processes. For a highly dynamic system like the cloud, provenance can be accurately detected and securely used in cloud digital forensic investigation activities. This paper proposes watchword oriented provenance cognition algorithm for the cloud environment. Additionally time-stamp based buffer verifying algorithm is proposed for securing the access to the detected cloud provenance. Performance analysis of the novel algorithms proposed here yields a desirable detection rate of 89.33% and miss rate of 8.66%. The securing algorithm successfully rejects 64% of malicious requests, yielding a cumulative frequency of 21.43 for MR.
机译:来源是有关系统数据和过程的起源和活动的派生日记信息。对于像云这样的高度动态的系统,可以准确地检测出处并在云数字取证调查活动中安全地使用来源。提出了面向云环境的面向词源识别的算法。另外,提出了基于时间戳的缓冲区验证算法,以确保对检测到的云源的访问安全。本文提出的新型算法的性能分析得出理想的检测率为89.33%,未命中率为8.66%。安全算法成功拒绝了64%的恶意请求,从而使MR的累积频率为21.43。

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