Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Authentication via keystroke dynamics
Proceedings of the 4th ACM conference on Computer and communications security
User authentication through keystroke dynamics
ACM Transactions on Information and System Security (TISSEC)
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 Identification Based on Handwritten Signatures with Haptic Information
EuroHaptics '08 Proceedings of the 6th international conference on Haptics: Perception, Devices and Scenarios
Homogeneous physio-behavioral visual and mouse-based biometric
ACM Transactions on Computer-Human Interaction (TOCHI)
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Keystroke typing characteristics is considered as one of the important biometric features that can be used to protect users against malicious attacks. In this paper we propose a statistical model for web authentication with keystroke typing characteristics based on Hidden Markov Model and Gaussian Modeling from Statistical Learning Theory. Our proposed model can substantially enhance the accuracy of the identity authentication by analyzing keystroke timing information of the username and password. Results of the experiments showed that our scheme achieved by far the best error rate of 2.54%.