Feature selection based hybrid anomaly intrusion detection system using K Means and RBF kernel function

Procedia Computer Science

Volumn 45, Issue C, 2015, Pages 428-435

  Ravale, Ujwala ^a   Marathe, Nilesh ^b   Padiya, Puja ^b  

^a Mumbai University   (India)

^b RAMRAO ADIK INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Intrusion detection system; K means clustering; RBF kernel; SVM classifier

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTER CRIME; DATA MINING; MERCURY (METAL); RADIAL BASIS FUNCTION NETWORKS; SECURITY OF DATA; SUPPORT VECTOR MACHINES;

ANOMALY INTRUSION DETECTION; ASSOCIATION RULE DISCOVERY; INTRUSION DETECTION SYSTEMS; K-MEANS CLUSTERING; K-MEANS CLUSTERING ALGORITHM; RBF KERNEL FUNCTION; RBF KERNELS; SVM CLASSIFIERS;

INTRUSION DETECTION;

EID: 84938578413     PISSN: None     EISSN: 18770509     Source Type: Conference Proceeding    
DOI: 10.1016/j.procs.2015.03.174     Document Type: Conference Paper

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