Systematic analysis of qualitative data in security

Hanan Hibshi
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Abstract

This tutorial will introduce participants to Grounded Theory, which is a qualitative framework to discover new theory from an empirical analysis of data. This form of analysis is particularly useful when analyzing text, audio or video artifacts that lack structure, but contain rich descriptions. We will frame Grounded Theory in the context of qualitative methods and case studies, which complement quantitative methods, such as controlled experiments and simulations. We will contrast the approaches developed by Glaser and Strauss, and introduce coding theory - the most prominent qualitative method for performing analysis to discover Grounded Theory. Topics include coding frames, first- and second-cycle coding, and saturation. We will use examples from security interview scripts to teach participants: developing a coding frame, coding a source document to discover relationships in the data, developing heuristics to resolve ambiguities between codes, and performing second-cycle coding to discover relationships within categories. Then, participants will learn how to discover theory from coded data. Participants will further learn about inter-rater reliability statistics, including Cohen's and Fleiss' Kappa, Krippendorf's Alpha, and Vanbelle's Index. Finally, we will review how to present Grounded Theory results in publications, including how to describe the methodology, report observations, and describe threats to validity.
安全定性数据的系统分析
本教程将向参与者介绍扎根理论,这是一个从数据实证分析中发现新理论的定性框架。这种形式的分析在分析缺乏结构但包含丰富描述的文本、音频或视频工件时特别有用。我们将在定性方法和案例研究的背景下构建扎根理论,这些方法和案例研究补充了定量方法,如对照实验和模拟。我们将对比Glaser和Strauss开发的方法,并介绍编码理论——执行分析以发现扎根理论的最突出的定性方法。主题包括编码帧,第一和第二循环编码,和饱和度。我们将使用来自安全面试脚本的示例来教参与者:开发编码框架,编写源文档以发现数据中的关系,开发启发式方法以解决代码之间的歧义,并执行第二循环编码以发现类别内的关系。然后,参与者将学习如何从编码数据中发现理论。参与者将进一步了解评分者之间的信度统计,包括Cohen和Fleiss的Kappa, Krippendorf的Alpha和Vanbelle的指数。最后,我们将回顾如何在出版物中呈现扎根理论结果,包括如何描述方法,报告观察结果,以及描述有效性的威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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