Window Functions in Rhythm Based Biometric Authentication
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50017072" target="_blank" >RIV/62690094:18450/20:50017072 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-45385-5_10" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-45385-5_10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-45385-5_10" target="_blank" >10.1007/978-3-030-45385-5_10</a>
Alternative languages
Result language
angličtina
Original language name
Window Functions in Rhythm Based Biometric Authentication
Original language description
Emerging new technologies and new threads entail additional security; therefore, biometric authentication is the key to protecting the passwords by classifying unique biometric features. One of the protocols recently proposed is the rhythm-based authentication dealing with the dominant frequency components of the keystroke signals. However, frequency component itself is not enough to understand the whole keystroke sequence; therefore, the characteristic of a password could only be analyzed by transformations providing the information of when which dominant frequency arises. In this paper, the biometric signal generated from keystroke data is divided into windows by various window functions and sizes for frequency and time localization. As a guide for signal processing in biometrics and biomedicine, we compared Hamming and Blackman widow functions with various sizes in short time Fourier transformations of the signals and found out that Blackman is more appropriate for biometric signal processing. © Springer Nature Switzerland AG 2020.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-030-45384-8
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
108-118
Publisher name
Springer
Place of publication
Cham
Event location
Granada, Spain
Event date
May 6, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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