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BotDet: A System for Real Time Botnet Command and Control Traffic Detection

Ghafir, Ibrahim; Prenosil, Vaclav; Hammoudeh, Mohammad; Baker, Thar; Jabbar, Sohail; Khalid, Shehzad; Jaf, Sardar

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Ibrahim Ghafir

Vaclav Prenosil

Mohammad Hammoudeh

Thar Baker

Sohail Jabbar

Shehzad Khalid

Sardar Jaf


Over the past decade, the digitization of services transformed the healthcare sector leading to a sharp rise in cybersecurity threats. Poor cybersecurity in the healthcare sector, coupled with high value of patient records attracted the attention of hackers. Sophisticated advanced persistent threats and malware have significantly contributed to increasing risks to the health sector. Many recent attacks are attributed to the spread of malicious software, e.g., ransomware or bot malware. Machines infected with bot malware can be used as tools for remote attack or even cryptomining. This paper presents a novel approach, called BotDet, for botnet Command and Control (C&C) traffic detection to defend against malware attacks in critical ultrastructure systems. There are two stages in the development of the proposed sytsem: (i) we have developed four detection modules to detect different possible techniques used in botnet C&C communications; (ii) we have designed a correlation framework to reduce the rate of false alarms raised by individual detection modules. Evaluation results show that BotDet balances the true positive rate and the false positive rate with 82.3% and 13.6% respectively. Furthermore, it proves BotDet capability of real time detection.

Journal Article Type Article
Acceptance Date May 26, 2018
Online Publication Date Jun 13, 2018
Publication Date Jul 30, 2018
Deposit Date Jun 12, 2018
Publicly Available Date Jul 26, 2018
Journal IEEE Access
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 6
Pages 38947-38958
Public URL


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