Verifying identity via keystroke characteristics
International Journal of Man-Machine Studies
Identity authentication based on keystroke latencies
Communications of the ACM
Independent component analysis: algorithms and applications
Neural Networks
Enhanced Password Authentication through Fuzzy Logic
IEEE Expert: Intelligent Systems and Their Applications
Typing Patterns: A Key to User Identification
IEEE Security and Privacy
User authentication through typing biometrics features
IEEE Transactions on Signal Processing
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
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Keystroke dynamics is unique specific characteristics used for user authentication problem. There are many researches to detect personal keystroke dynamics and authenticate user based on these characteristics. Most researches study on either the key press durations and multiple key latencies (typing time) or key-pressed forces (pressure-based typing) to find the owned personal motif (unique specific characteristic). This paper approaches to extract keystroke dynamics by using independent component analysis (ICA) through a standardized bio-matrix from typing sound signals which contain both typing time and typing force information. The ICA representation of keystroke dynamics is effective for authenticating user in our experiments. The experimental results show that the proposed keystroke dynamics extraction solution is feasible and reliable to solve user authentication problem with false acceptance rate (FAR) 4.12% and false rejection rate (FRR) 5.55%.