Open Access

ARTICLE

User Interface-Based Repeated Sequence Detection Method for Authentication

Shin Jin Kang¹, Soo Kyun Kim^2,*

1 School of Games, Hongik University, Sejong, 30016, Korea
2 Department of Computer Engineering, Jeju National University, Jeju, 63243, Korea

* Corresponding Author: Soo Kyun Kim. Email:

Intelligent Automation & Soft Computing 2023, 35(3), 2573-2588. https://doi.org/10.32604/iasc.2023.029893

Received 14 March 2022; Accepted 21 April 2022; Issue published 17 August 2022

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.

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Keywords

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