Highly Robust Analysis of Keystroke Dynamics Measurements

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00438100" target="_blank" >RIV/67985807:_____/15:00438100 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21460/15:00225042

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Highly Robust Analysis of Keystroke Dynamics Measurements

Original language description

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 withsmall 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 bythe 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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2015

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

SAMI 2015

ISBN

978-1-4799-8220-2

ISSN

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e-ISSN

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Number of pages

6

Pages from-to

133-138

Publisher name

IEEE Hungary Section

Place of publication

Budapest

Event location

Herl'any

Event date

Jan 22, 2015

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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