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Increased reproducibility and comparability of data leak evaluations using ExOT

机译:使用ExOT提高数据泄漏评估的可重复性和可比性

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As computing systems are increasingly shared among different users or application domains, researchers have intensified their efforts to detect possible data leaks. In particular, many investigations highlight the vulnerability of systems w.r.t. covert and side channel attacks. However, the effort required to reproduce and compare different results has proven to be high. Therefore, we present a novel methodology for covert channel evaluation. In addition, we introduce the Experiment Orchestration Toolkit ExOT, which provides software tools to efficiently execute the methodology.Our methodology ensures that the covert channel analysis yields expressive results that can be reproduced and allow the comparison of the threat potential of different data leaks. ExOT is a software bundle that consists of easy to extend C++ libraries and Python packages. These libraries and packages provide tools for the generation and execution of experiments, as well as the analysis of the experimental data. Therefore, ExOT decreases the engineering effort needed to execute our novel methodology. We verify these claims with an extensive evaluation of four different covert channels on an Intel Haswell and an ARMv8 based platform. In our evaluation, we derive capacity bounds and show achievable throughputs to compare the threat potential of these different covert channels.
机译:随着计算系统越来越多地在不同用户或应用程序域之间共享,研究人员已加紧努力以发现可能的数据泄漏。特别是,许多调查都着重指出了w.r.t.秘密和边道攻击。但是,事实证明,重现和比较不同结果需要付出很大的努力。因此,我们提出了一种用于隐蔽渠道评估的新颖方法。此外,我们推出了实验编排工具包ExOT,该工具包提供了有效执行该方法的软件工具。我们的方法可确保隐蔽通道分析产生可再现的表达性结果,并可以比较不同数据泄漏的潜在威胁。 ExOT是一个软件包,由易于扩展的C ++库和Python软件包组成。这些库和程序包提供了用于生成和执行实验以及分析实验数据的工具。因此,ExOT减少了执行我们的新方法所需的工程工作量。我们通过对Intel Haswell和基于ARMv8的平台上的四个不同秘密通道的广泛评估来验证这些说法。在我们的评估中,我们得出容量界限并显示可实现的吞吐量,以比较这些不同隐蔽渠道的潜在威胁。

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