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Reseach Article

User Authentication using Keystroke Dynamics

Published on August 2019 by Vishesh Mishra, Raghav Gupta, Raghav Gupta, J. C. Patni
International Conference on Recent Trends in Science, Technology, Management and Social Development
Foundation of Computer Science USA
ICRTSTMSD2018 - Number 1
August 2019
Authors: Vishesh Mishra, Raghav Gupta, Raghav Gupta, J. C. Patni
c998e0b0-ca7c-4d43-9779-f547fb6c5749

Vishesh Mishra, Raghav Gupta, Raghav Gupta, J. C. Patni . User Authentication using Keystroke Dynamics. International Conference on Recent Trends in Science, Technology, Management and Social Development. ICRTSTMSD2018, 1 (August 2019), 29-33.

@article{
author = { Vishesh Mishra, Raghav Gupta, Raghav Gupta, J. C. Patni },
title = { User Authentication using Keystroke Dynamics },
journal = { International Conference on Recent Trends in Science, Technology, Management and Social Development },
issue_date = { August 2019 },
volume = { ICRTSTMSD2018 },
number = { 1 },
month = { August },
year = { 2019 },
issn = 0975-8887,
pages = { 29-33 },
numpages = 5,
url = { /proceedings/icrtstmsd2018/number1/30846-1806/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Science, Technology, Management and Social Development
%A Vishesh Mishra
%A Raghav Gupta
%A Raghav Gupta
%A J. C. Patni
%T User Authentication using Keystroke Dynamics
%J International Conference on Recent Trends in Science, Technology, Management and Social Development
%@ 0975-8887
%V ICRTSTMSD2018
%N 1
%P 29-33
%D 2019
%I International Journal of Computer Applications
Abstract

"User Authentication Using Keystroke Dynamics". It is a method to get the user authentication on an android application by using the keystroke dynamics of the user using Artificial Neural Networks with the help of Error Back Propagation algorithm. In this application the user enters the password 30 times and databases are used to record 45 factors that describes a user's keystroke patterns like di-graph, dwell time, tri-graph, flight time, finger size, button pressure, coordinate values which can be seen by the user in real time. Once this is done the data is taken and put in an Artificial Neural Network and trained using Error back propagation Algorithm. This process done over time produces trained set off weights that would produces an already calculated value in the output layer. This data from the network is again stored in a separate table which is then used to check the authentication of the user typing the password.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Networks Error Back Propagation Algorithm Keystroke Dynamics Database Systems Mobile Phones Passwords Pins (personal Identification Numbers) Android Biometric Authentication