Improving performance of intrusion detection system using ensemble methods and feature selection.
Ngoc Tu PhamErnest FooSuriadi SuriadiHelen JeffreyHassan Fareed M. LahzaPublished in: ACSW (2018)
Keyphrases
- intrusion detection system
- ensemble methods
- feature selection
- feature subset
- intrusion detection
- ensemble feature selection
- ensemble learning
- prediction accuracy
- ensemble classification
- network security
- benchmark datasets
- random forests
- anomaly detection
- ensemble classifier
- distributed intrusion detection
- network traffic
- machine learning methods
- decision trees
- generalization ability
- base classifiers
- text categorization
- feature selection algorithms
- classification accuracy
- random forest
- bootstrap sampling
- text classification
- feature set
- machine learning
- model selection
- feature extraction
- multiple models
- multi class
- dimensionality reduction
- computer systems
- feature space
- gene selection
- support vector machine
- support vector
- classification models
- association rules
- regression problems
- base learners
- data mining
- data mining techniques
- misuse detection
- naive bayes
- decision tree ensembles