Username and password verification through keystroke dynamics

Abstract

Most computer systems rely on usernames and passwords as a mechanism for access control and authentication of authorized users. These credential sets offer marginal protection to a broad scope of applications with differing levels of sensitivity. Traditional physiological biometric systems such as fingerprint, face, and iris recognition are not readily deployable in remote authentication schemes. Keystroke dynamics provide the ability to combine the ease of use of username/password schemes with the increased trustworthiness associated with biometrics. Our research extends previous work on keystroke dynamics by incorporating shift-key patterns. The system is capable of operating at various points on a traditional ROC curve depending on application specific security needs. A 1% False Accept Rate is attainable at a 14% False Reject Rate for high security systems. An Equal Error Rate of 5% can be obtained in lower security systems. As a username password authentication scheme, our approach decreases the penetration rate associated with compromised passwords by 95--99%

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