Tappert, C.C., Villani, M. and Cha, S. (2009) Keystroke Biometric Identification and Authentication on Long-Text Input. Behavioral Biometrics for Human Identification: Intelligent Applications, IGI Global, 342-367.

has been cited by the following article:

• TITLE: Keyboard Dependency of Personal Identification Performance by Keystroke Dynamics in Free Text Typing

  AUTHORS: Yoshitomo Matsubara, Toshiharu Samura, Haruhiko Nishimura

  KEYWORDS: Keystroke Dynamics, Biometrics, Information Security, Keyboard Dependency

  JOURNAL NAME: Journal of Information Security, Vol.6 No.3, July 14, 2015

  ABSTRACT: We have proposed some methods for feature extraction and identification that enable identification of individuals through long-text input as an important topic in keystroke dynamics research. As to the robustness in practical circumstances, there exists a question on the keystroke dynamics how much the recognition accuracy is influenced by the change of keyboard. By comparing the performance in the cases of using the same keyboard and different keyboards, the dependencies on keyboards are evaluated through three implemented experiments for subjects. As a result, it is found that we do not need to worry about the keyboard difference for users whose typing skills reach high level with about 900 or more letters in 5 minutes, and only for the remaining users it would be necessary to register their profile data with respect to each keyboard they use in order to avoid recognition accuracy degradation.