Biometric Swiping on Touchscreens

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F15%3A50004178" target="_blank" >RIV/62690094:18450/15:50004178 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-319-24369-6_16" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-24369-6_16</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-24369-6_16" target="_blank" >10.1007/978-3-319-24369-6_16</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Biometric Swiping on Touchscreens

Popis výsledku v původním jazyce

Touchscreen devices have become very popular in the last decade and eased our modern life. It is now possible to automatically log in to any web page connected to our touchscreen phones, such as social networks, e-commerce sites and even mobile banking. Given these facts, the emerging touchscreen technology brings out a potential security issue: weakness of authentication protocols. Therefore, we put forward a biometric enhancement on "swiping" authentication, which is one of the options to log in a touchscreen phone however with the lowest security. We created a ghost password by extracting the features of coordinates and swipe durations to use them as the inputs of the Levenberg-Marquardt based neural network and adaptive neuro-fuzzy classifiers which both discriminate real attempts from fraud attacks after training.

Název v anglickém jazyce

Biometric Swiping on Touchscreens

Popis výsledku anglicky

Touchscreen devices have become very popular in the last decade and eased our modern life. It is now possible to automatically log in to any web page connected to our touchscreen phones, such as social networks, e-commerce sites and even mobile banking. Given these facts, the emerging touchscreen technology brings out a potential security issue: weakness of authentication protocols. Therefore, we put forward a biometric enhancement on "swiping" authentication, which is one of the options to log in a touchscreen phone however with the lowest security. We created a ghost password by extracting the features of coordinates and swipe durations to use them as the inputs of the Levenberg-Marquardt based neural network and adaptive neuro-fuzzy classifiers which both discriminate real attempts from fraud attacks after training.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Computer information systems and industrial management (CISIM 2015)

ISSN

0302-9743

e-ISSN

—

Svazek periodika

9339

Číslo periodika v rámci svazku

2015

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

11

Strana od-do

193-203

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-84959223936