The journal of digital forensics, security and law · 2015 · 29 citations · 17 references
ComputingComputer ScienceCybersecurityComputer SecurityMachine LearningNetwork SecurityBot DetectionIntrusion DetectionNetwork Traffic AnalysisPeer-to-peer NetworkingPeer-to-peer NetworksPeer-to-peer SystemsAnti-detection TechniquesBotnet DetectionBotnet InfrastructureBotnet Traffic AnalysisBotnet Traffic DetectionData Flow PatternsHierarchical Clustering
Botnets have evolved to become one of the most serious threats to the Internet and there is substantial research on both botnets and botnet detection techniques. This survey reviewed the history of botnets and botnet detection techniques. The survey showed traditional botnet detection techniques rely on passive techniques, primarily honeypots, and that honeypots are not effective at detecting peer-to-peer and other decentralized botnets. Furthermore, the detection techniques aimed at decentralized and peer-to-peer botnets focus on detecting communications between the infected bots. Recent research has shown hierarchical clustering of flow data and machine learning are effective techniques for detecting botnet peer-to-peer traffic.
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BotHunter: detecting malware infection through IDS-driven dialog correlation
Guofei Gu, Phillip Porras, Vinod Yegneswaran et al. · 2007 · 692 citations
The Honeynet Project: trapping the hackers
L. Spitzner · IEEE Security & Privacy · 2003 · 545 citations