风险模型的图形与表格符号:关于文本标签和复杂性的作用

Katsiaryna Labunets, F. Massacci, A. Tedeschi
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引用次数: 7

摘要

【背景】安全风险评估方法在行业中多采用表格形式来表示评估结果,而学术界则主张采用图形方法。对硕士学生的实验表明,表格符号比符号符号更能理解安全风险。[目的]我们研究文本标签和简洁的uml风格表示法是否可以提高可理解性。[方法]我们报告了一项在线可理解性实验的结果,该实验涉及61名平均工作经验为9年的专业人员,在该实验中,我们比较了理解以表格、uml风格与文本标签和标志性图形建模符号表示的安全风险评估的能力。[结果]表列记法在查全率和查准率上仍然是最容易理解的概念。然而,文本标签的存在确实提高了参与者的准确率和召回率,而不是标志性的图形模型。[结论]表格表示法比图形表示法更能支持简单和复杂的安全风险可理解性问题的正确信息提取,而文本标签则有帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Graphical vs. Tabular Notations for Risk Models: On the Role of Textual Labels and Complexity
[Background] Security risk assessment methods in industry mostly use a tabular notation to represent the assessment results whilst academic works advocate graphical methods. Experiments with MSc students showed that the tabular notation is better than an iconic graphical notation for the comprehension of security risks. [Aim] We investigate whether the availability of textual labels and terse UML-style notation could improve comprehensibility. [Method] We report the results of an online comprehensibility experiment involving 61 professionals with an average of 9 years of working experience, in which we compared the ability to comprehend security risk assessments represented in tabular, UML-style with textual labels, and iconic graphical modeling notations. [Results] Tabular notation are still the most comprehensible notion in both recall and precision. However, the presence of textual labels does improve the precision and recall of participants over iconic graphical models. [Conclusion] Tabular representation better supports extraction of correct information of both simple and complex comprehensibility questions about security risks than the graphical notation but textual labels help.
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