Hidden frequency feature in electronic signatures

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Hidden frequency feature in electronic signatures

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Hidden frequency feature in electronic signatures

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

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

—

Počet stran výsledku

12

Strana od-do

145-156

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Morioka; Japan

Datum konání akce

2. 8. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000387771300013