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Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices

N.Krishnaraj 1

Section:Research Paper, Product Type: Journal Paper
Volume-3 , Issue-3 , Page no. 98-101, Mar-2015

Online published on Mar 31, 2015

Copyright © N.Krishnaraj . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: N.Krishnaraj, “Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.98-101, 2015.

MLA Style Citation: N.Krishnaraj "Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices." International Journal of Computer Sciences and Engineering 3.3 (2015): 98-101.

APA Style Citation: N.Krishnaraj, (2015). Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices. International Journal of Computer Sciences and Engineering, 3(3), 98-101.

BibTex Style Citation:
@article{_2015,
author = {N.Krishnaraj},
title = {Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2015},
volume = {3},
Issue = {3},
month = {3},
year = {2015},
issn = {2347-2693},
pages = {98-101},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=429},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=429
TI - Feature Extraction Techniques in Keystroke Dynamics for Securing Personal Devices
T2 - International Journal of Computer Sciences and Engineering
AU - N.Krishnaraj
PY - 2015
DA - 2015/03/31
PB - IJCSE, Indore, INDIA
SP - 98-101
IS - 3
VL - 3
SN - 2347-2693
ER -

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Abstract

This paper presents a novel approach used to identify and analyze the features of keystroke dynamics. Keystroke dynamics is a authentication technique which aims to identify the person based on the behavioral characteristic (Typing Rhythms). The keystroke data like Duration, latency and digraph are measured using statistical techniques. The user keystroke patterns are collected and further it is analyzed to identify the quality features that will be given to feature subset selection for selecting the dominant features. The extracted features will be given to the feature subset selection for identifying dominant features.

Key-Words / Index Term

Biometrics,Feature Extraction , Keystroke Dynamics , Latency, Digraph

References

1. Marcus Karnan, N.Krishnaraj , “ Biopassword – A Keystroke Dynamics Approach to Secure Mobile Devices” , in IEEE International Conference on computational Intelligence and Computing Research ( ICCCIC), pp.1-4,2010.
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