Conversion methods for symbolic features: A comparison applied to an intrusion detection problem

Expert Systems with Applications

Volumn 36, Issue 7, 2009, Pages 10612-10617

  Hernandez Pereira E ^a   Suarez Romero J A ^a   Fontenla Romero, O ^a   Alonso Betanzos, A ^a  

^a UNIVERSITY OF A CORUÑA   (Spain)

Author keywords

Anomaly detection; Intrusion detection systems; Machine learning; Symbolic features

Indexed keywords

ANOMALY DETECTION; CLASSIFICATION METHODS; CONDITIONAL PROBABILITIES; CONVERSION METHODS; DATA SETS; INDICATOR VARIABLES; INTRUSION DETECTION SYSTEMS; MACHINE LEARNING; MACHINE LEARNING METHODS; MULTI-LAYER FEED-FORWARD NEURAL NETWORKS; NETWORK TRAFFICS; NUMERICAL VALUES; POTENTIAL SOLUTIONS; SYMBOLIC ATTRIBUTES; SYMBOLIC FEATURES; VALUE METHODS;

COMPUTER CRIME; FEEDFORWARD NEURAL NETWORKS; INTERNET; MULTILAYER NEURAL NETWORKS; NETWORK LAYERS; NUMERICAL METHODS; ROBOT LEARNING;

INTRUSION DETECTION;

EID: 67349099506     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.02.054     Document Type: Article

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