Sound data sets and methods for web security research

Victor Le Pochat

Published in 2023

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Sound research practices are the foundation of valid, reliable, and trustworthy research results. In the context of web security research, the importance of measurements that yield the empirical real-world data for analyzing and improving security on the web emphasizes the need to use sound data sets and methods that allow these measurements to be accurate, comprehensive, representative, and transparent. In this dissertation, we discuss three case studies in web security that have affinity with the discipline of meta-research, which critically evaluates these research practices and proposes new methods to improve and refine the way in which research is conducted. The three presented case studies contribute to critically analyzing current web security data sets or systems that are commonly held to be reliable, while we also propose improved methods as well as discuss data set considerations.

BibTeX:

@phdthesis{LePochat2023PhDThesis,
author = {Le Pochat, Victor},
title = {Sound data sets and methods for web security research},
school = {KU Leuven},
year = 2023,
month = 5
}