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arXiv 2401.04446cs.SE
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数据流图如何影响软件安全分析:一项实证实验

How Dataflow Diagrams Impact Software Security Analysis: an Empirical Experiment

Simon Schneider, Nicolás E. Díaz Ferreyra, Pierre-Jean Quéval, Georg Simhandl, Uwe Zdun, Riccardo Scandariato

AI总结:

本研究通过实证实验探讨数据流图(DFD)对软件安全分析的影响,发现提供DFD和追踪信息能显著提升分析师的任务正确率(41%)和证据正确率(315%),并指出三个开放挑战。

摘要:

软件系统模型在整个软件开发生命周期中都被使用。特别是数据流图(DFD),是用于安全分析的成熟资源。许多技术,如威胁建模,都基于被分析应用的DFD。然而,它们在安全分析环境中对分析师表现的影响此前尚未被探讨。在本文中,我们展示了一项实证实验的结果,该实验旨在调查这种影响。采用组内设计,参与者被要求为给定的微服务应用解决与安全相关的任务。在控制条件下,参与者必须手动检查源代码。在模型支持条件下,他们还获得了被分析应用的DFD以及将模型项链接到源代码中工件的追踪信息。我们发现,参与者(n = 24)在模型支持条件下正确回答分析任务的表现显著更好(分析正确率提高41%)。此外,报告使用所提供追踪信息的参与者在为其答案提供证据方面表现更好(证据正确率提高315%)。最后,基于实验中获得的见解,我们确定了使用DFD进行安全分析的三个开放挑战。

英文摘要:

Models of software systems are used throughout the software development lifecycle. Dataflow diagrams (DFDs), in particular, are well-established resources for security analysis. Many techniques, such as threat modelling, are based on DFDs of the analysed application. However, their impact on the performance of analysts in a security analysis setting has not been explored before. In this paper, we present the findings of an empirical experiment conducted to investigate this effect. Following a within-groups design, participants were asked to solve security-relevant tasks for a given microservice application. In the control condition, the participants had to examine the source code manually. In the model-supported condition, they were additionally provided a DFD of the analysed application and traceability information linking model items to artefacts in source code. We found that the participants (n = 24) performed significantly better in answering the analysis tasks correctly in the model-supported condition (41% increase in analysis correctness). Further, participants who reported using the provided traceability information performed better in giving evidence for their answers (315% increase in correctness of evidence). Finally, we identified three open challenges of using DFDs for security analysis based on the insights gained in the experiment.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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