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Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.11 P.943-983


Botnet detection techniques: review, future trends, and issues

Author(s):  Ahmad Karim, Rosli Bin Salleh, Muhammad Shiraz, Syed Adeel Ali Shah, Irfan Awan, Nor Badrul Anuar

Affiliation(s):  Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia; more

Corresponding email(s):   ahmadkarim@um.edu.my

Key Words:  Botnet detection, Anomaly detection, Network security, Attack, Defense, Taxonomy

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Ahmad Karim, Rosli Bin Salleh, Muhammad Shiraz, Syed Adeel Ali Shah, Irfan Awan, Nor Badrul Anuar. Botnet detection techniques: review, future trends, and issues[J]. Journal of Zhejiang University Science C, 2014, 15(11): 943-983.

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author="Ahmad Karim, Rosli Bin Salleh, Muhammad Shiraz, Syed Adeel Ali Shah, Irfan Awan, Nor Badrul Anuar",
journal="Journal of Zhejiang University Science C",
publisher="Zhejiang University Press & Springer",

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%T Botnet detection techniques: review, future trends, and issues
%A Ahmad Karim
%A Rosli Bin Salleh
%A Muhammad Shiraz
%A Syed Adeel Ali Shah
%A Irfan Awan
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1300242

T1 - Botnet detection techniques: review, future trends, and issues
A1 - Ahmad Karim
A1 - Rosli Bin Salleh
A1 - Muhammad Shiraz
A1 - Syed Adeel Ali Shah
A1 - Irfan Awan
A1 - Nor Badrul Anuar
J0 - Journal of Zhejiang University Science C
VL - 15
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SP - 943
EP - 983
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1300242

In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service (DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.



Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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