Intelligent biometric pattern password authentication systems for touchscreens

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F15%3A50003813" target="_blank" >RIV/62690094:18450/15:50003813 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S0957417415002948" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0957417415002948</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2015.04.052" target="_blank" >10.1016/j.eswa.2015.04.052</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Intelligent biometric pattern password authentication systems for touchscreens

Popis výsledku v původním jazyce

Given the recent developments in alternative authentication interfaces for smartphones, tablets and touchscreen laptops, one of the mostly selected method is the pattern passwords. Basically, the users that prefer this method, draw a pattern between thenodes to open the lock in lieu of entering an alphanumeric password. Although drawing a pattern seems easier than typing a password, it has a major security drawback since it can be very easy to be stolen. Therefore, this paper proposes some novel theoretical ideas with artificial intelligence methods, to improve security of pattern password authentication, using touching durations as biometric traits. What we put forward is the utilization of three different neural network based algorithms to verify logins with one novel histogram-based technique in a hidden interface for enrollment, training and verification. Inspired by the keystroke recognition models, the touch time and durations are extracted to create a ghost password. Moreover,

Název v anglickém jazyce

Intelligent biometric pattern password authentication systems for touchscreens

Popis výsledku anglicky

Given the recent developments in alternative authentication interfaces for smartphones, tablets and touchscreen laptops, one of the mostly selected method is the pattern passwords. Basically, the users that prefer this method, draw a pattern between thenodes to open the lock in lieu of entering an alphanumeric password. Although drawing a pattern seems easier than typing a password, it has a major security drawback since it can be very easy to be stolen. Therefore, this paper proposes some novel theoretical ideas with artificial intelligence methods, to improve security of pattern password authentication, using touching durations as biometric traits. What we put forward is the utilization of three different neural network based algorithms to verify logins with one novel histogram-based technique in a hidden interface for enrollment, training and verification. Inspired by the keystroke recognition models, the touch time and durations are extracted to create a ghost password. Moreover,

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Expert systems with applications

ISSN

0957-4174

e-ISSN

—

Svazek periodika

42

Číslo periodika v rámci svazku

17-18

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9

Strana od-do

6286-6294

Kód UT WoS článku

000356122000002

EID výsledku v databázi Scopus

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