ML Anthology

Keystroke Dynamics for User Authentication

Yu Zhong, Yunbin Deng, Anil K. Jain
CVPRW 2012 pp. 117-123
doi:10.1109/CVPRW.2012.6239225 /cvprw/2012/zhong2012cvprw-keystroke/

Abstract

In this paper we investigate the problem of user authentication using keystroke biometrics. A new distance metric that is effective in dealing with the challenges intrinsic to keystroke dynamics data, i.e., scale variations, feature interactions and redundancies, and outliers is proposed. Our keystroke biometrics algorithms based on this new distance metric are evaluated on the CMU keystroke dynamics benchmark dataset and are shown to be superior to algorithms using traditional distance metrics.

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Text

Zhong et al. "Keystroke Dynamics for User Authentication." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2012. doi:10.1109/CVPRW.2012.6239225

Markdown

[Zhong et al. "Keystroke Dynamics for User Authentication." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2012.](https://mlanthology.org/cvprw/2012/zhong2012cvprw-keystroke/) doi:10.1109/CVPRW.2012.6239225

BibTeX

@inproceedings{zhong2012cvprw-keystroke,
  title     = {{Keystroke Dynamics for User Authentication}},
  author    = {Zhong, Yu and Deng, Yunbin and Jain, Anil K.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2012},
  pages     = {117-123},
  doi       = {10.1109/CVPRW.2012.6239225},
  url       = {https://mlanthology.org/cvprw/2012/zhong2012cvprw-keystroke/}
}