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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM23831
Volume:
7 |
6 |
Jun 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Botnets pose a significant threat to network security, enabling various malicious activities such as distributed denial-of-service (DDoS) attacks, spam campaigns, and data theft. Traditional methods of botnet detection based solely on network or host analysis have limitations in effectively detecting sophisticated botnets. Hybrid botnet detection techniques, which combine both network and host analysis, have emerged as a promising approach to enhance the accuracy and efficiency of botnet detection. This survey paper aims to provide an overview of recent advancements in hybrid botnet detection techniques, highlighting their strengths, limitations, and future research directions.
KEYWORDS
Publication Date
6/19/2023
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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