0438100 - ÚI 2015 RIV HU eng C - Conference Paper (international conference)
Kalina, Jan - Schlenker, A. - Kutílek, P.
Highly Robust Analysis of Keystroke Dynamics Measurements.
SAMI 2015. Budapest: IEEE Hungary Section, 2015, s. 133-138. ISBN 978-1-4799-8220-2.
[SAMI 2015. International Symposium on Applied Machine Intelligence and Informatics /13./. Herl'any (SK), 22.01.2015-24.01.2015]
Grant - others:GA ČR(CZ) GA13-01930S; CESNET Development Fund(CZ) 494/2013; SVV(CZ) 260034
Institutional support: RVO:67985807
Keywords : robust classification * regularization * keystroke dynamics
Subject RIV: IN - Informatics, Computer Science

Standard classification procedures of both data mining and multivariate statistics are sensitive to the presence of outlying values. In this paper, we propose new algorithms for computing regularized versions of linear discriminant analysis for data with small sample sizes in each group. Further, we propose a highly robust version of a regularized linear discriminant analysis. The new method denoted as MWCD-L2-LDA is based on the idea of implicit weights assigned to individual observations, inspired by the minimum weighted covariance determinant estimator. Classification performance of the new method is illustrated on a detailed analysis of our pilot study of authentication methods on computers, using individual typing characteristics by means of keystroke dynamics.
Permanent Link: http://hdl.handle.net/11104/0241581