使用隐马尔可夫模型的击键生物识别用户验证

M. Ali, Kutub Thakur, C. Tappert, Meikang Qiu
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引用次数: 16

摘要

指纹、虹膜、DNA等生物识别系统成为用户认证的常用方法。与这些生物识别系统相比,击键生物识别认证系统由于准确性较低而没有得到太多关注。使用不同的生成分类器和判别分类器对击键生物识别进行了大量的研究。由于隐马尔可夫模型在语音识别中取得了巨大的成功,本研究对隐马尔可夫模型在按键动态中的应用进行了研究。本文提出了一种新的基于1-子态隐马尔可夫模型的用户验证技术。为了验证所提系统的有效性,进行了大量的实验,所提系统的准确率达到80%。
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Keystroke Biometric User Verification Using Hidden Markov Model
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.
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