A novel SVM-kNN-PSO ensemble method for intrusion detection system

Applied Soft Computing Journal

Volumn 38, Issue , 2016, Pages 360-372

  Aburomman, Abdulla Amin ^a   Ibne Reaz, Mamun Bin ^a  

^a UNIVERSITI KEBANGSAAN MALAYSIA   (Malaysia)

Author keywords

Ensemble; k NN; LUS; PSO; SVM; Weighted majority voting (WMV)

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; LUTETIUM; MERCURY (METAL); NEAREST NEIGHBOR SEARCH; OPTIMIZATION;

CLASSIFICATION ACCURACY; COMBINATION OF CLASSIFIERS; ENSEMBLE; INTRUSION DETECTION SYSTEMS; PSO; SVM; WEIGHTED MAJORITY ALGORITHM; WEIGHTED MAJORITY VOTING (WMV);

INTRUSION DETECTION;

EID: 84945936408     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2015.10.011     Document Type: Article

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