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Big Data and Internet of Things Security and Forensics: Challenges and Opportunities Read chapter Read first chapter

2019 | OriginalPaper | Chapter

A Bibliometric Analysis of Botnet Detection Techniques

Authors : Shehu Amina, Raul Vera, Tooska Dargahi, Ali Dehghantanha

Published in: Handbook of Big Data and IoT Security

Publisher: Springer International Publishing

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Abstract

Botnets are rising as a platform for many unlawful cyber activities such as Distributed Denial of Service (DDoS) attacks, malware dissemination, phishing, click fraud, and so on. As of late, detecting botnet has been an intriguing research topic in relation to cybercrime analysis and cyber-threat prevention. This paper is an analysis of publications related to botnet detection techniques. We analyse 194 botnet related papers published between 2009 and 2018 in the ISI Web of Science database. Seven (7) criteria have been used for this analysis to detect highly-cited articles, most impactful journals, current research areas, most active researchers and institutions in the field. It was noted that the average number of publications related to botnet detection have been reduced recently, which could be because of overwhelming existing literature in the field. Asia is the most active and most productive continent in botnet research and computer science is the research area with most publications related to botnet detection as expected.

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previous chapter Bibliometric Analysis on the Rise of Cloud Security
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Metadata
Title
A Bibliometric Analysis of Botnet Detection Techniques
Authors
Shehu Amina
Raul Vera
Tooska Dargahi
Ali Dehghantanha
Copyright Year
2019
Book
Handbook of Big Data and IoT Security

Print ISBN: 978-3-030-10542-6

Electronic ISBN: 978-3-030-10543-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-10543-3_15

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