Keystroke Biometric User Verification Using Hidden Markov Model

• Published in: 2016 IEEE 3rd International Conference on Cyber Security and Cloud Computing (CSCloud) pp. 204 - 209
• Main Authors: Ali, Md Liakat, Thakur, Kutub, Tappert, Charles C., Meikang Qiu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2016
• Subjects: Authentication; Biological system modeling; Biometrics (access control); Feature extraction; Hidden Markov Model; Hidden Markov models; Identification; Keyboards; Keystroke Biometrics; Training; Verification
• DOI: 10.1109/CSCloud.2016.23

Biometric systems such as fingerprint, iris, DNA became popular methods in user authentication. Compared to these biometric systems, keystroke biometric authentication systems have not gained so much attention because of lower accuracy compared to other biometric systems. A number of researches have been conducted on keystroke biometric using different generative and discriminative classifiers. As Hidden Markov Models have proven a great success in voice recognition, this study investigates Hidden Markov Models in keystroke dynamic. This paper proposes a novel user verification technique using 1-substate Hidden Markov Model through keystroke dynamic. To verify the effectiveness of the proposed system, extensive experiments have been conducted and 80% accuracy was achieved by the proposed system.