@inproceedings{Lopatka:2009aa,
	Abstract = {We present a novel method for performing non-invasive biometric
analysis on habitual keystroke patterns using a vibration-based
feature space.  With the increasing availability of 3-D accelerometer
chips in laptop computers, conventional methods using time vectors may
be augmented using a distinct feature space.  In these preliminary
results, we demonstrate the efficacy of a vibration-based feature
space for both authentication and identification paradigms.
Discussion of the generation of this feature space, the learning of
typing profiles, and evaluation in several experimental paradigms is
provided. Several suggestions for the further development of vibration
information in keystroke dynamics are also discussed.
},
	Author = {Lopatka, Martin and Peetz, Maria-Hendrike},
	Booktitle = {Proceedings of the 18th Annual Belgian-Dutch Conference on Machine Learning},
	Keywords = {Machine Learning, Keystroke Analysis, Computer Security, Biometrics, Authentication, Sudden Motion Sensor},
	Month = {May},
	Pages = {75-80},
	Title = {Vibration Sensitive Keystroke Analysis},
	Year = {2009}}