Hidden frequency feature in electronic signatures
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F16%3A50005024" target="_blank" >RIV/62690094:18450/16:50005024 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-42007-3_13" target="_blank" >http://dx.doi.org/10.1007/978-3-319-42007-3_13</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-42007-3_13" target="_blank" >10.1007/978-3-319-42007-3_13</a>
Alternative languages
Result language
angličtina
Original language name
Hidden frequency feature in electronic signatures
Original language description
Forensics is a science discipline that deals with collecting evidence in crime scene investigation. However if we're dealing with signatures, the crime scene is the signed paper itself. Therefore, for any kind of investigation, there should be a sample and a master signature to benchmark the similarities and differences. The characteristics of a master signature could easily be identified by forensics techniques, yet it is still infeasible for electronic signatures due to ease of copy-pasting. Through the emerging touchscreen technologies, the features of the signatures could be stealthily extracted and stored while the user is signing. Given these facts, the novelty we put forward in this paper is a feature extraction method using short time Fourier transformations to identify frequencies of a simple master signature. We subsequently presented the spectrogram analysis revealing the differences between the original and fake signatures. Finally a validation method for the analysis of the spectrograms is introduced which resulted in a significant gap between real and fraud signatures for various window sizes.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
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
978-3-319-42006-6
ISSN
0302-9743
e-ISSN
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Number of pages
12
Pages from-to
145-156
Publisher name
Springer
Place of publication
Berlin
Event location
Morioka; Japan
Event date
Aug 2, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000387771300013