A hybrid network intrusion detection framework based on random forests and weighted k-means

Ain Shams Engineering Journal

Volumn 4, Issue 4, 2013, Pages 753-762

  Elbasiony, Reda M ^a   Sallam, Elsayed A ^a   Eltobely, Tarek E ^a   Fahmy, Mahmoud M ^a  

^a Tanta University   (Egypt)

Author keywords

Computer network security; Data mining; Intrusion detection; k Means; Random forests

Indexed keywords

ANOMALY DETECTION; CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; DATA MINING; DECISION TREES; INTRUSION DETECTION; NETWORK SECURITY;

CLASSIFICATION ALGORITHM; INTRUSION PATTERNS; K-MEANS; KNOWLEDGE DISCOVERY AND DATA MININGS; MINING CLASSIFICATION; NETWORK CONNECTION; NETWORK INTRUSIONS; RANDOM FORESTS;

K-MEANS CLUSTERING;

EID: 84887824664     PISSN: 20904479     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asej.2013.01.003     Document Type: Article

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