A Survey of Keystroke Dynamics Biometrics <s> Adaptive Threshold. <s> This document presents the application of biometrics to strength conventional passwords. We show methods to analyze and compare users' keystroke patterns to be able to verify their identity when entering the password into a computer system. The problem's difficulty arises from the fact that only a very limited amount data is available and that new users can come and others may leave the system meantime. That is we are not allowed to re-evaluate all users' data during the application. We show test results based on 2400 records collected from 25 users of different typing ability. <s> BIB001 </s> A Survey of Keystroke Dynamics Biometrics <s> Adaptive Threshold. <s> The keystroke patterns produced during typing have been shown to be unique biometric signatures. Therefore, these patterns can be used as digital signatures to verify the identity of computer users remotely over the Internet or locally at a specific workstation. In particular, keystroke recognition can enhance the username and password security model by monitoring the way that these strings are typed. To this end, this paper proposes a novel up--up keystroke latency (UUKL) feature and compares its performance with existing features using a Gaussian mixture model (GMM)-based verification system that utilizes an adaptive and user-specific threshold based on the leave-one-out method (LOOM). The results show that the UUKL feature significantly outperforms the commonly used key hold-down time (KD) and down--down keystroke latency (DDKL) features. Overall, the inclusion of the UUKL feature led to an equal error rate (EER) of 4.4% based on a database of 41 users, which is a 2.1% improvement as compared to the existing features. Comprehensive results are also presented for a two-stage authentication system that has shown significant benefits. Lastly, due to many inconsistencies in previous works, a formal keystroke protocol is recommended that consolidates a number of parameters concerning how to improve performance, reliability, and accuracy of keystroke-recognition systems. <s> BIB002
Instead of updating the keystroke reference template, BIB001 proposed to readjust the matching threshold. This method circumvents the complexity of retraining sample data over potentially complex algorithm. In BIB002 , threshold is repeatedly reassessed upon every successful authenticated user access. Users are also given two trials to be validated, with the assumption that legitimate users are more likely to pass an authentication test; this ends up with high adaptation accuracy.