Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi

Recently, BYOD or Bring Your Own Device has become one of the most popular methods for enterprises to provide mobility and flexibility in workplaces. The emergence of new technologies and features of mobile devices makes them integral part of every aspect of daily business activities. On the other h...

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Main Author: Eslahi, Meisam
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2017
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/19881/
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author Eslahi, Meisam
author_facet Eslahi, Meisam
author_sort Eslahi, Meisam
building UiTM Institutional Repository
collection Online Access
description Recently, BYOD or Bring Your Own Device has become one of the most popular methods for enterprises to provide mobility and flexibility in workplaces. The emergence of new technologies and features of mobile devices makes them integral part of every aspect of daily business activities. On the other hand, mobile devices are not well protected compared to computers and their users pay less attention to security updates and solutions , therefore, these new capabilities (e.g. high internet speed and processing power) have motivated the attackers to migrate to mobile infrastructures. Thus, mobile security has become a crucial issue in BYOD or Bring Your Own Device as the employees use their own mobile devices to access an organization data and systems. The mobile attacks and threats come in different forms, such as viruses and worms. However, Mobile Botnets or MoBots are more dangerous as they pose serious threats to mobile devices and communication networks. Bot and Botnets are sophisticated form of organized cyber-crime, which infect different targets (e.g. computers or mobile devices) without attracting the users’ attention, which subsequently communicates with each other by using a Command and Control (C&C) mechanism. The main intention of Botnets is to steal the private and personal information (e.g. Zeus and Zitmo) or sensitive information of organizations (e.g. Flame and Stuxnet), thus, several techniques such as encryption and use of standard protocols (e.g. HTTP and Port 80) employed by Botmasters to develop foolproof C&C mechanism which are difficult to detect.
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spelling uitm-198812018-06-08T02:11:13Z https://ir.uitm.edu.my/id/eprint/19881/ Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi Eslahi, Meisam Malaysia Recently, BYOD or Bring Your Own Device has become one of the most popular methods for enterprises to provide mobility and flexibility in workplaces. The emergence of new technologies and features of mobile devices makes them integral part of every aspect of daily business activities. On the other hand, mobile devices are not well protected compared to computers and their users pay less attention to security updates and solutions , therefore, these new capabilities (e.g. high internet speed and processing power) have motivated the attackers to migrate to mobile infrastructures. Thus, mobile security has become a crucial issue in BYOD or Bring Your Own Device as the employees use their own mobile devices to access an organization data and systems. The mobile attacks and threats come in different forms, such as viruses and worms. However, Mobile Botnets or MoBots are more dangerous as they pose serious threats to mobile devices and communication networks. Bot and Botnets are sophisticated form of organized cyber-crime, which infect different targets (e.g. computers or mobile devices) without attracting the users’ attention, which subsequently communicates with each other by using a Command and Control (C&C) mechanism. The main intention of Botnets is to steal the private and personal information (e.g. Zeus and Zitmo) or sensitive information of organizations (e.g. Flame and Stuxnet), thus, several techniques such as encryption and use of standard protocols (e.g. HTTP and Port 80) employed by Botmasters to develop foolproof C&C mechanism which are difficult to detect. Institute of Graduate Studies, UiTM 2017 Book Section PeerReviewed text en https://ir.uitm.edu.my/id/eprint/19881/2/ABS_MEISAM%20ESLAHI%20TDRA%20VOL%2012%20IGS%2017.pdf Eslahi, Meisam (2017) Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi. (2017) In: The Doctoral Research Abstracts. IGS Biannual Publication, 12 (12). Institute of Graduate Studies, UiTM, Shah Alam.
spellingShingle Malaysia
Eslahi, Meisam
Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title_full Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title_fullStr Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title_full_unstemmed Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title_short Cooperative network behavior analysis model for mobile HTTP botnet detection / Meisam Eslahi
title_sort cooperative network behavior analysis model for mobile http botnet detection / meisam eslahi
topic Malaysia
url https://ir.uitm.edu.my/id/eprint/19881/