A study of touching behavior for authentication in touch screen smart devices

With the increased popularity of touch screen mobile phones, touch gesture behavior is becoming more and more important. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we...

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Main Authors:	Alariki, Ala Abdulhakim, Abdul Manaf, Azizah, Khan, Sheroz
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers, Inc. 2016
Subjects:	TK5101 Telecommunication. Including telegraphy, radio, radar, television
Online Access:	http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/1/51300_A_Study_of_Touching_Behavior_for_Authentication.pdf http://irep.iium.edu.my/51300/2/51300_A_Study_of_Touching_Behavior_for_Authentication_SCOPUS.pdf

id	iium-51300
recordtype	eprints
spelling	iium-513002016-12-30T07:51:33Z http://irep.iium.edu.my/51300/ A study of touching behavior for authentication in touch screen smart devices Alariki, Ala Abdulhakim Abdul Manaf, Azizah Khan, Sheroz TK5101 Telecommunication. Including telegraphy, radio, radar, television With the increased popularity of touch screen mobile phones, touch gesture behavior is becoming more and more important. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on these touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the android operation system. Based on these preliminary experiments we concentrated on the Random Forest classifier to differentiate multiple users. Our results show that combining all features such as touch direction, finger pressure, finger size and acceleration correctly classified touch behavior on an android phone with 98.14% accuracy. Institute of Electrical and Electronics Engineers, Inc. 2016 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/51300/1/51300_A_Study_of_Touching_Behavior_for_Authentication.pdf application/pdf en http://irep.iium.edu.my/51300/2/51300_A_Study_of_Touching_Behavior_for_Authentication_SCOPUS.pdf Alariki, Ala Abdulhakim and Abdul Manaf, Azizah and Khan, Sheroz (2016) A study of touching behavior for authentication in touch screen smart devices. In: 2016 International Conference on Intelligent Systems Engineering (ICISE), 15th-17th March 2016, Islamabad, Pakistan. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7475123&filter%3DAND%28p_IS_Number%3A7475106%29 10.1109/INTELSE.2016.7475123
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK5101 Telecommunication. Including telegraphy, radio, radar, television
spellingShingle	TK5101 Telecommunication. Including telegraphy, radio, radar, television Alariki, Ala Abdulhakim Abdul Manaf, Azizah Khan, Sheroz A study of touching behavior for authentication in touch screen smart devices
description	With the increased popularity of touch screen mobile phones, touch gesture behavior is becoming more and more important. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on these touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the android operation system. Based on these preliminary experiments we concentrated on the Random Forest classifier to differentiate multiple users. Our results show that combining all features such as touch direction, finger pressure, finger size and acceleration correctly classified touch behavior on an android phone with 98.14% accuracy.
format	Conference or Workshop Item
author	Alariki, Ala Abdulhakim Abdul Manaf, Azizah Khan, Sheroz
author_facet	Alariki, Ala Abdulhakim Abdul Manaf, Azizah Khan, Sheroz
author_sort	Alariki, Ala Abdulhakim
title	A study of touching behavior for authentication in touch screen smart devices
title_short	A study of touching behavior for authentication in touch screen smart devices
title_full	A study of touching behavior for authentication in touch screen smart devices
title_fullStr	A study of touching behavior for authentication in touch screen smart devices
title_full_unstemmed	A study of touching behavior for authentication in touch screen smart devices
title_sort	study of touching behavior for authentication in touch screen smart devices
publisher	Institute of Electrical and Electronics Engineers, Inc.
publishDate	2016
url	http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/ http://irep.iium.edu.my/51300/1/51300_A_Study_of_Touching_Behavior_for_Authentication.pdf http://irep.iium.edu.my/51300/2/51300_A_Study_of_Touching_Behavior_for_Authentication_SCOPUS.pdf
first_indexed	2023-09-18T21:12:37Z
last_indexed	2023-09-18T21:12:37Z
_version_	1777411353056641024

A study of touching behavior for authentication in touch screen smart devices

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