PassViz: A Visualisation System for Analysing Leaked Passwords
Sam Parker, Haiyue Yuan, Shujun Li

TL;DR
PassViz is a novel visualization system that combines edit distance and t-SNE to analyze leaked passwords in 2-D, aiding researchers in discovering patterns and improving password security.
Contribution
Introduces PassViz, a new visualization method that integrates edit distance with t-SNE for analyzing leaked passwords, available as a command-line tool and GUI.
Findings
Effective visual analysis of large-scale leaked password datasets
Discovery of previously unknown password patterns
Enhanced insights for improving password security
Abstract
Passwords remain the most widely used form of user authentication, despite advancements in other methods. However, their limitations, such as susceptibility to attacks, especially weak passwords defined by human users, are well-documented. The existence of weak human-defined passwords has led to repeated password leaks from websites, many of which are of large scale. While such password leaks are unfortunate security incidents, they provide security researchers and practitioners with good opportunities to learn valuable insights from such leaked passwords, in order to identify ways to improve password policies and other security controls on passwords. Researchers have proposed different data visualisation techniques to help analyse leaked passwords. However, many approaches rely solely on frequency analysis, with limited exploration of distance-based graphs. This paper reports PassViz,…
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Taxonomy
TopicsUser Authentication and Security Systems · Data Visualization and Analytics · Time Series Analysis and Forecasting
