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User Authentication Method Based on Keystroke Dynamics and Mouse Dynamics with Scene-Irrelated Features in Hybrid
Xiujuan Wang1, Yutong Shi1, Kangfeng Zheng2
1Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
Sensors (Basel, Switzerland)
|September 9, 2022
Summary
This study introduces a novel user authentication method, SIURUA, to enhance accuracy in hybrid environments. SIURUA effectively fuses scene-irrelated and user-related features for reliable identification.
Area of Science:
- Computer Science
- Cybersecurity
- Human-Computer Interaction
Background:
- User authentication accuracy is challenged in hybrid scenes due to varying user behaviors.
- Simulating user actions across different operational contexts is complex.
- Existing methods struggle with dynamic user status changes in diverse environments.
Purpose of the Study:
- To develop an advanced user authentication method for hybrid scenes.
- To address the challenges posed by user operation changes and status variations.
- To improve the reliability and accuracy of biometric authentication systems.
Main Methods:
- Feature extraction from keystroke and mouse movement data.
- Identification and selection of scene-irrelated features with low environmental correlation.
- Fusion of scene-irrelated features with user-related features for comprehensive user identification.
Main Results:
- The proposed SIURUA method demonstrates improved user authentication accuracy in hybrid scenes.
- Experimental validation achieved an authentication accuracy of 84%.
- The fusion strategy effectively integrates diverse feature sets for robust identification.
Conclusions:
- SIURUA offers a promising solution for accurate user authentication in complex, hybrid environments.
- The method's ability to handle dynamic user behavior enhances security.
- This approach contributes to more secure and adaptive biometric authentication systems.
