User Password Repetitive Patterns Analysis and Visualization
Authors: Xiaoying Yu, Qi Liao

Date: 2016
Publication: Information and Computer Security, Vol 24, No 1
Page(s): 93 - 115
Publisher: Emerald Group Publishing Limited
Source 1: http://people.cst.cmich.edu/liao1q/papers/ICS-06-2015-0026.pdf
Source 2: https://doi.org/10.1108/ICS-06-2015-0026 - Subscription or payment required

Abstract or Summary:
Purpose Passwords have been designed to protect individual privacy and security and widely used in almost every area of our life. The strength of passwords is therefore critical to the security of our systems. However, due to the explosion of user accounts and increasing complexity of password rules, users are struggling to find ways to make up sufficiently secure yet easy-to-remember passwords. This paper aims to investigate whether there are repetitive patterns when users choose passwords and how such behaviors may affect us to rethink password security policy.

Design/methodology/approach The authors develop a model to formalize the password repetitive problem and design efficient algorithms to analyze the repeat patterns. To help security practitioners to analyze patterns, the authors design and implement a lightweight, Web-based visualization tool for interactive exploration of password data.

Findings Through case studies on a real-world leaked password data set, the authors demonstrate how the tool can be used to identify various interesting patterns, e.g. shorter substrings of the same type used to make up longer strings, which are then repeated to make up the final passwords, suggesting that the length requirement of password policy does not necessarily increase security.

Originality/value The contributions of this study are two-fold. First, the authors formalize the problem of password repetitive patterns by considering both short and long substrings and in both directions, which have not yet been considered in past. Efficient algorithms are developed and implemented that can analyze various repeat patterns quickly even in large data set. Second, the authors design and implement four novel visualization views that are particularly useful for exploration of password repeat patterns, i.e. the character frequency charts view, the short repeat heatmap view, the long repeat parallel coordinates view and the repeat word cloud view.


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