Using naive Bayes with AdaBoost to enhance network anomaly intrusion detection

Proceedings - 3rd International Conference on Intelligent Networks and Intelligent Systems, ICINIS 2010

Volumn , Issue , 2010, Pages 486-489

  Li, Wei ^a   Li, QingXia ^b  

^a DONGGUAN UNIVERSITY OF TECHNOLOGY   (China)

^b Huali Science and Technology College   (China)

Author keywords

AdaBoost; Detection rate; False positive rate; Naive Bayes

Indexed keywords

ADABOOST; ANOMALY DETECTION; ANOMALY INTRUSION DETECTION; DETECTION RATE; DETECTION RATES; FALSE POSITIVE; FALSE POSITIVE RATES; INTRUSION DETECTION SYSTEMS; MACHINE LEARNING ALGORITHMS; NAIVE BAYES; NETWORK ANOMALIES; NETWORK-BASED; RANDOM DATA; SET OF RULES; TRAFFIC BEHAVIOR; WEAK LEARNER;

ADAPTIVE BOOSTING; COMPUTER CRIME; INTELLIGENT NETWORKS; INTELLIGENT SYSTEMS; LEARNING SYSTEMS;

INTRUSION DETECTION;

EID: 79951763931     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICINIS.2010.133     Document Type: Conference Paper

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