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User Interface-Based Repeated Sequence Detection Method for Authenticationopen access
- Authors
- Kang, S.J.; Kim, S.K.
- Issue Date
- 1-Jan-2023
- Publisher
- Tech Science Press
- Keywords
- Authentication; keystroke; keystroke-level model (KLM); mouse dynamics
- Citation
- Intelligent Automation and Soft Computing, v.35, no.3, pp 2573 - 2588
- Pages
- 16
- Journal Title
- Intelligent Automation and Soft Computing
- Volume
- 35
- Number
- 3
- Start Page
- 2573
- End Page
- 2588
- ISSN
- 1079-8587
2326-005X
- Abstract
- In this paper, we propose an authentication method that use mouse and keystroke dynamics to enhance online privacy and security. The proposed method identifies personalized repeated user interface (UI) sequences by analyzing mouse and keyboard data. To this end, an Apriori algorithm based on the keystroke-level model (KLM) of the human–computer interface domain was used. The proposed system can detect repeated UI sequences based on KLM for authentication in the software. The effectiveness of the proposed method is verified through access testing using commercial applications that require intensive UI interactions. The results show using our cognitive mouse-and-keystroke dynamics system can complement authentication at the application level. © 2023, Tech Science Press. All rights reserved.
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Collections - School of Games > Game Software Major > 1. Journal Articles
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Related Researcher
- Kang, Shin Jin
- Game (Major in Game Software)