Visible to the public Systematic Analysis of Qualitative Data in Security

TitleSystematic Analysis of Qualitative Data in Security
Publication TypeConference Paper
Year of Publication2016
AuthorsHibshi, Hanan
Conference NameProceedings of the Symposium and Bootcamp on the Science of Security
Date PublishedApril 2016
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4277-3
Keywordscontrol theory, grounded theory, pubcrawl, qualitative, Resiliency, security, security analysis
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.

URLhttps://dl.acm.org/doi/10.1145/2898375.2898387
DOI10.1145/2898375.2898387
Citation Keyhibshi_systematic_2016