Identifying important characteristics in the KDD99 intrusion detection dataset by feature selection using a hybrid approach

ICT 2010: 2010 17th International Conference on Telecommunications

Volumn , Issue , 2010, Pages 552-558

  Araújo, Nelcileno ^a   De Oliveira, Ruy ^b   Ferreira, Ed'Wilson ^b   Shinoda, Ailton Akira ^c   Bhargava, Bharat ^d  

^a FEDERAL UNIVERSITY OF MATO GROSSO   (Brazil)

^b Instituto Federal de Mato Grosso   (Brazil)

^c SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^d Purdue University   (United States)

Author keywords

Hybrid approach; Information gain ratio; K means; KDD99. feature selection

Indexed keywords

ANOMALOUS BEHAVIOR; DATA SETS; EVALUATION RESULTS; FEATURE SELECTION; FINE TUNING; HYBRID APPROACH; INFORMATION GAIN RATIO; INTRUSION DETECTION SYSTEMS; K-MEANS; OPTIMAL SUBSETS;

COMPUTER CRIME; FEATURE EXTRACTION; OPTIMIZATION;

INTRUSION DETECTION;

EID: 77954556689     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTEL.2010.5478852     Document Type: Conference Paper

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