Cooperative network behaviour analysis model for mobile Botnet detection

Recently, the mobile devices are well integrated with Internet and widely used by normal users and organizations which employ Bring Your Own Device technology. On the other hand, the mobile devices are less protected in comparison to computers. Therefore, the mobile devices and networks have now bec...

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Published in:ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics
Main Author: Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992034514&doi=10.1109%2fISCAIE.2016.7575046&partnerID=40&md5=f2e5a02bdef0827f24f13571e01e6409
id 2-s2.0-84992034514
spelling 2-s2.0-84992034514
Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
Cooperative network behaviour analysis model for mobile Botnet detection
2016
ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics


10.1109/ISCAIE.2016.7575046
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992034514&doi=10.1109%2fISCAIE.2016.7575046&partnerID=40&md5=f2e5a02bdef0827f24f13571e01e6409
Recently, the mobile devices are well integrated with Internet and widely used by normal users and organizations which employ Bring Your Own Device technology. On the other hand, the mobile devices are less protected in comparison to computers. Therefore, the mobile devices and networks have now become attractive targets for attackers. Amongst several types of mobile threats, the mobile HTTP Botnets can be considered as one of the most sophisticated attacks. A HTTP Bots stealthily infect mobile devices and periodically communicate with their controller called Botmaster. Although the Bots hide their activities amongst the normal web flows, their periodic pattern has been used as a measure to detect their activities. In this paper we propose a cooperative network behaviour analysis model to identify the level of periodicity posed by mobile Bots. Finally three metrics is proposed to detect Mobile HTTP Botnets based on similarity and correlation of their group activities. Test results show that the propose model can efficiently classify communication patterns into several periodicity categories and detect mobile Botnets. © 2016 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
spellingShingle Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
Cooperative network behaviour analysis model for mobile Botnet detection
author_facet Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
author_sort Eslahi M.; Yousefi M.; Naseri M.V.; Yussof Y.M.; Tahir N.M.; Hashim H.
title Cooperative network behaviour analysis model for mobile Botnet detection
title_short Cooperative network behaviour analysis model for mobile Botnet detection
title_full Cooperative network behaviour analysis model for mobile Botnet detection
title_fullStr Cooperative network behaviour analysis model for mobile Botnet detection
title_full_unstemmed Cooperative network behaviour analysis model for mobile Botnet detection
title_sort Cooperative network behaviour analysis model for mobile Botnet detection
publishDate 2016
container_title ISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics
container_volume
container_issue
doi_str_mv 10.1109/ISCAIE.2016.7575046
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992034514&doi=10.1109%2fISCAIE.2016.7575046&partnerID=40&md5=f2e5a02bdef0827f24f13571e01e6409
description Recently, the mobile devices are well integrated with Internet and widely used by normal users and organizations which employ Bring Your Own Device technology. On the other hand, the mobile devices are less protected in comparison to computers. Therefore, the mobile devices and networks have now become attractive targets for attackers. Amongst several types of mobile threats, the mobile HTTP Botnets can be considered as one of the most sophisticated attacks. A HTTP Bots stealthily infect mobile devices and periodically communicate with their controller called Botmaster. Although the Bots hide their activities amongst the normal web flows, their periodic pattern has been used as a measure to detect their activities. In this paper we propose a cooperative network behaviour analysis model to identify the level of periodicity posed by mobile Bots. Finally three metrics is proposed to detect Mobile HTTP Botnets based on similarity and correlation of their group activities. Test results show that the propose model can efficiently classify communication patterns into several periodicity categories and detect mobile Botnets. © 2016 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
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record_format scopus
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