A Static Approach towards Mobile Botnet Detection

The use of mobile devices, including smartphones, tablets, smart watches and notebooks are increasing day by day in our societies. They are usually connected to the Internet and offer nearly the same functionality, same memory and same speed like a PC. To get more benefits from these mobile devices,...

Full description

Bibliographic Details
Main Authors:	Shahid, Anwar, Jasni, Mohamad Zain, Inayat, Zakira, Ul Haq, Riaz, Ahmad, Karim, Jaber, Aws Naser
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2016
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/16286/ http://umpir.ump.edu.my/id/eprint/16286/ http://umpir.ump.edu.my/id/eprint/16286/1/A%20Static%20Approach%20towards%20Mobile%20Botnet.pdf http://umpir.ump.edu.my/id/eprint/16286/7/fskkp1.pdf

id	ump-16286
recordtype	eprints
spelling	ump-162862019-10-15T07:32:05Z http://umpir.ump.edu.my/id/eprint/16286/ A Static Approach towards Mobile Botnet Detection Shahid, Anwar Jasni, Mohamad Zain Inayat, Zakira Ul Haq, Riaz Ahmad, Karim Jaber, Aws Naser QA76 Computer software The use of mobile devices, including smartphones, tablets, smart watches and notebooks are increasing day by day in our societies. They are usually connected to the Internet and offer nearly the same functionality, same memory and same speed like a PC. To get more benefits from these mobile devices, applications should be installed in advance. These applications are available from third party websites, such as google play store etc. In existing mobile devices operating systems, Android is very easy to attack because of its open source environment. Android OS use of open source facilty attracts malware developers to target mobile devices with their new malicious applications having botnet capabilities. Mobile botnet is one of the crucial threat to mobile devices. In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. In this technique, the given features are extracted from android applications in order to build a machine learning classifier for detection of mobile botnet attacks. Initial experiments conducted on a known and recently updated dataset: UNB ISCX Android botnet dataset, having the combination of 14 different malware families, shows the efficiency of our approach. The given research is in progress. IEEE 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/16286/1/A%20Static%20Approach%20towards%20Mobile%20Botnet.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/16286/7/fskkp1.pdf Shahid, Anwar and Jasni, Mohamad Zain and Inayat, Zakira and Ul Haq, Riaz and Ahmad, Karim and Jaber, Aws Naser (2016) A Static Approach towards Mobile Botnet Detection. In: IEEE 3rd International Conference on Electronic Design (ICED 2016), 11-12 August 2016 , Phuket, Thailand. pp. 563-567.. ISBN 978-1-5090-2160-4 https://doi.org/10.1109/ICED.2016.7804708
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Shahid, Anwar Jasni, Mohamad Zain Inayat, Zakira Ul Haq, Riaz Ahmad, Karim Jaber, Aws Naser A Static Approach towards Mobile Botnet Detection
description	The use of mobile devices, including smartphones, tablets, smart watches and notebooks are increasing day by day in our societies. They are usually connected to the Internet and offer nearly the same functionality, same memory and same speed like a PC. To get more benefits from these mobile devices, applications should be installed in advance. These applications are available from third party websites, such as google play store etc. In existing mobile devices operating systems, Android is very easy to attack because of its open source environment. Android OS use of open source facilty attracts malware developers to target mobile devices with their new malicious applications having botnet capabilities. Mobile botnet is one of the crucial threat to mobile devices. In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. In this technique, the given features are extracted from android applications in order to build a machine learning classifier for detection of mobile botnet attacks. Initial experiments conducted on a known and recently updated dataset: UNB ISCX Android botnet dataset, having the combination of 14 different malware families, shows the efficiency of our approach. The given research is in progress.
format	Conference or Workshop Item
author	Shahid, Anwar Jasni, Mohamad Zain Inayat, Zakira Ul Haq, Riaz Ahmad, Karim Jaber, Aws Naser
author_facet	Shahid, Anwar Jasni, Mohamad Zain Inayat, Zakira Ul Haq, Riaz Ahmad, Karim Jaber, Aws Naser
author_sort	Shahid, Anwar
title	A Static Approach towards Mobile Botnet Detection
title_short	A Static Approach towards Mobile Botnet Detection
title_full	A Static Approach towards Mobile Botnet Detection
title_fullStr	A Static Approach towards Mobile Botnet Detection
title_full_unstemmed	A Static Approach towards Mobile Botnet Detection
title_sort	static approach towards mobile botnet detection
publisher	IEEE
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/16286/ http://umpir.ump.edu.my/id/eprint/16286/ http://umpir.ump.edu.my/id/eprint/16286/1/A%20Static%20Approach%20towards%20Mobile%20Botnet.pdf http://umpir.ump.edu.my/id/eprint/16286/7/fskkp1.pdf
first_indexed	2023-09-18T22:21:48Z
last_indexed	2023-09-18T22:21:48Z
_version_	1777415705730220032

A Static Approach towards Mobile Botnet Detection

Similar Items