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dc.contributor.authorKarim, A.*
dc.contributor.authorBin Salleh, R.*
dc.contributor.authorShiraz, M.*
dc.contributor.authorShah, S.A.A.*
dc.contributor.authorAwan, Irfan U.*
dc.contributor.authorAnuar, N.B.*
dc.date.accessioned2016-11-23T18:25:42Z
dc.date.available2016-11-23T18:25:42Z
dc.date.issued2014
dc.identifier.citationKarim A, Bin Salleh R, Shiraz M et al (2014) Botnet detection techniques: review, future trends, and issues. Journal of Zhejiang University-Science C-Computers & Electronics. 15(11): 943-983.
dc.identifier.urihttp://hdl.handle.net/10454/10659
dc.descriptionNo
dc.description.abstractIn 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.
dc.description.sponsorshipUniversity of Malaya, Malaysia (No. FP034-2012A)en_US
dc.relation.isreferencedbyhttps://doi.org/10.1631/jzus.C1300242
dc.subjectBotnet detection
dc.subject; Anomaly detection
dc.subject; Network security
dc.subject; Attack
dc.subject; Defense
dc.subject; Taxonomy
dc.subject; Remote-control behavior
dc.subject; Anomaly detection
dc.subject; Command
dc.subject; Dark
dc.titleBotnet detection techniques: review, future trends, and issues
dc.status.refereedYes
dc.typeArticle
dc.type.versionNo full-text in the repository


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