少即是多?:利用类比迁移研究实例在安全研究中的作用

Ashwini Rao, Hanan Hibshi, T. Breaux, Jean-Michel Lehker, Jianwei Niu
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引用次数: 4

摘要

信息系统开发人员和管理员经常忽略关键的安全需求和最佳实践。这可能是由于缺乏工具和技术,使从业者能够根据他们的特定环境定制安全知识。为了探索新的安全方法的影响,我们必须提高研究安全工具和方法对软件和系统开发的影响的能力。在本文中,我们提出了一个实验的早期发现,以评估安全训练刺激中使用的示例的数量和类型可以影响安全问题解决的程度。为了推动本研究,我们从心理学的类比迁移理论中提出假设。自变量包括问题面和模式的数量,因变量是答案的准确性。我们的研究结果显示,当示例的数量和类型不同时,性能没有统计学上的显著差异。我们讨论了该领域的局限性、有效性的威胁以及未来研究的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Less is more?: investigating the role of examples in security studies using analogical transfer
Information system developers and administrators often overlook critical security requirements and best practices. This may be due to lack of tools and techniques that allow practitioners to tailor security knowledge to their particular context. In order to explore the impact of new security methods, we must improve our ability to study the impact of security tools and methods on software and system development. In this paper, we present early findings of an experiment to assess the extent to which the number and type of examples used in security training stimuli can impact security problem solving. To motivate this research, we formulate hypotheses from analogical transfer theory in psychology. The independent variables include number of problem surfaces and schemas, and the dependent variable is the answer accuracy. Our study results do not show a statistically significant difference in performance when the number and types of examples are varied. We discuss the limitations, threats to validity and opportunities for future studies in this area.
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