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2021 | OriginalPaper | Buchkapitel

Studies of Keyboard Patterns in Passwords: Recognition, Characteristics and Strength Evolution

verfasst von : Kunyu Yang, Xuexian Hu, Qihui Zhang, Jianghong Wei, Wenfen Liu

Erschienen in: Information and Communications Security

Verlag: Springer International Publishing

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Abstract

Keyboard patterns are widely used in password construction, as they can be easily memorized with the aid of positions on the keyboard. Consequently, keyboard-pattern-based passwords has being the target in many dictionary attack models. However, most of the existing researches relies only on recognition methods defining keyboard pattern structures empirically or even manually. As a result, only those infamous keyboard patterns such as qwerty are recognized and many potential structures are not specified. Besides, there are limited studies focusing on the characteristics of keyboard patterns.
In this paper, we deal with the problem of recognizing and analyzing keyboard patterns in a systematic approach. Firstly, we put forward a general recognition method that can pick out keyboard patterns form passwords automatically. Next, a comprehensive study of keyboard pattern characteristics is presented, which reveals a great deal of amazing facts about the preference for passwords based on keyboard patterns, such as: (1) More than half of the pattern-based passwords are completely composed by keyboard patterns; (2) The frequency distribution of the keyboard patterns satisfies the PDF-Zipf model; (3) Users prefer to use keyboard patterns consisted by horizontal continuous keys or those characters whose physical location are on the upper left of the keyboard. We further evaluate the security of keyboard-pattern-based passwords by employing the PCFG-base cracking technique. The experimental results indicate that the keyboard patterns can reduce the security of passwords.

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Metadaten
Titel
Studies of Keyboard Patterns in Passwords: Recognition, Characteristics and Strength Evolution
verfasst von
Kunyu Yang
Xuexian Hu
Qihui Zhang
Jianghong Wei
Wenfen Liu
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-86890-1_9

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