Network anomaly detection by cascading k-Means clustering and C4.5 decision tree algorithm

Procedia Engineering

Volumn 30, Issue , 2012, Pages 174-182

  Muniyandi, Amuthan Prabakar ^a   Rajeswari, R ^b   Rajaram, R ^a  

^a THIAGARAJAR COLLEGE OF ENGINEERING   (India)

^b Government College of Pharmacy   (India)

Author keywords

Anomaly detection; C4.5 decision tree; k Means clustering

Indexed keywords

ANOMALY DETECTION; ANOMALY DETECTION METHODS; ANOMALY DETECTION SYSTEMS; C4.5 DECISION TREE ALGORITHM; C4.5 DECISION TREE METHOD; DECISION BOUNDARY; EUCLIDEAN DISTANCE; FALSE ALARM RATE; HIGH DETECTION RATE; K CLUSTER; K-MEANS; K-MEANS CLUSTERING; K-MEANS CLUSTERING METHOD; MALICIOUS ACTIVITIES; NETWORK ANOMALY DETECTION; NETWORK ENVIRONMENTS; NETWORK INTRUSION DETECTION SYSTEMS;

COMMUNICATION; SYSTEMS ANALYSIS;

DECISION TREES;

EID: 84859053923     PISSN: 18777058     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.proeng.2012.01.849     Document Type: Conference Paper

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