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Pattern Password Authentication Based on Touching Location

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F15%3A50004177" target="_blank" >RIV/62690094:18450/15:50004177 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007/978-3-319-24834-9_46" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-24834-9_46</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-24834-9_46" target="_blank" >10.1007/978-3-319-24834-9_46</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Pattern Password Authentication Based on Touching Location

  • Original language description

    Pattern passwords are one of the embedded authentication method of touchscreen devices, however it has some major drawbacks which briefly are identifiability and imitability. The password of the user is noticeable when entering the pattern due to shiningcircles. Therefore, what we put forward in this paper is a novel biometric implementation of a hidden system to pattern password authentication for increasing password security. As opposed to general research concept which extracts touch or keystroke durations, we focused on the touching coordinates calculated the distance of the line between the constant pattern node and the touched place as well as the angle. Using these inputs, we trained the neural network by Gauss-Newton and Levenberg-Marquardt algorithms and conducted the experiments with these trained classifiers.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Intelligent data engineering and automated learning (IDEAL 2015)

  • ISBN

    978-3-319-24833-2

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    395-403

  • Publisher name

    Springer

  • Place of publication

    Berlin

  • Event location

    Wroclaw

  • Event date

    Oct 14, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article