A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log
Crime; Cybersecurity; Denial-of-service attack; HIgh speed networks; Internet of things; Machine learning; Network security; Personal computing; Botmaster; Botnet detections; Botnets; Cyber-attacks; High-speed Networks; Introduction; Log.; Machine-learning; Network traffic; Related works; Botnet
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-270192023-05-29T17:38:44Z A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log Ibrahim Z.-A. Razali R.A. Ismail S.A. Azhar I.H.K. Rahim F.A. Azilan A.M.A. 57203863738 35146685400 56943570600 58109599200 57350579500 58109295900 Crime; Cybersecurity; Denial-of-service attack; HIgh speed networks; Internet of things; Machine learning; Network security; Personal computing; Botmaster; Botnet detections; Botnets; Cyber-attacks; High-speed Networks; Introduction; Log.; Machine-learning; Network traffic; Related works; Botnet Cyber-attacks are a common issue in this modern era because of the introduction of high-speed networks and the use of new technologies like Internet of Things (IoT) devices, which fuel the rapid expansion of cyber-attack. One of the common cyber-attacks is botnet attacks. Hackers use botnet attacks to exploit newly discovered vulnerabilities in order to conduct intensive scraping, distributed denial of service (DDoS) attacks, and other large-scale cybercrime. With their adaptable and dynamic character, botnets work with a botmaster to plan their activities, modify their codes, and update the bots regularly to avoid detection. Researchers use numerous techniques to detect the botnet. However, botmasters nowadays have improved due to avoiding security in detection. As the communication can leave traces that allow researchers to detect the botnet's existence, this paper will review 15 related works on botnet detection that utilize machine learning to predict the botnet communication with the command-and-control (C&C or C2) center based on the network traffic log. This paper summarizes the related works based on the dataset, environment, botnet type, features employed, and machine learning techniques. � 2022 IEEE. Final 2023-05-29T09:38:44Z 2023-05-29T09:38:44Z 2022 Conference Paper 10.1109/ICOCO56118.2022.10031803 2-s2.0-85148442424 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148442424&doi=10.1109%2fICOCO56118.2022.10031803&partnerID=40&md5=459fd12cc11b9157a3fb97fcea07d8c9 https://irepository.uniten.edu.my/handle/123456789/27019 204 209 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Crime; Cybersecurity; Denial-of-service attack; HIgh speed networks; Internet of things; Machine learning; Network security; Personal computing; Botmaster; Botnet detections; Botnets; Cyber-attacks; High-speed Networks; Introduction; Log.; Machine-learning; Network traffic; Related works; Botnet |
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57203863738 |
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57203863738 Ibrahim Z.-A. Razali R.A. Ismail S.A. Azhar I.H.K. Rahim F.A. Azilan A.M.A. |
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Conference Paper |
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Ibrahim Z.-A. Razali R.A. Ismail S.A. Azhar I.H.K. Rahim F.A. Azilan A.M.A. |
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Ibrahim Z.-A. Razali R.A. Ismail S.A. Azhar I.H.K. Rahim F.A. Azilan A.M.A. A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
author_sort |
Ibrahim Z.-A. |
title |
A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
title_short |
A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
title_full |
A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
title_fullStr |
A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
title_full_unstemmed |
A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log |
title_sort |
review of machine learning botnet detection techniques based on network traffic log |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
_version_ |
1806425551316975616 |
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13.18916 |