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

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

Research output: Contribution to journalArticlepeer-review


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 system: 1) we have developed four detection modules to detect different possible techniques used in botnet C&C communications and 2) 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.
Original languageEnglish
Pages (from-to)38947 - 38958
Number of pages11
JournalIEEE Access
Publication statusPublished - 13 Jun 2018


Dive into the research topics of 'BotDet: A System for Real Time Botnet Command and Control Traffic Detection'. Together they form a unique fingerprint.

Cite this