A tree-based stacking ensemble technique with feature selection for network intrusion detection.
Md. Mamunur RashidJoarder KamruzzamanTasadduq ImamSantoso WibowoSteven GordonPublished in: Appl. Intell. (2022)
Keyphrases
- network intrusion detection
- feature selection
- ensemble learning
- base classifiers
- intrusion detection
- anomaly detection
- network intrusion
- artificial immune
- fraud detection
- wrapper feature selection
- ensemble classifier
- feature set
- text categorization
- ensemble methods
- multi class
- feature ranking
- network anomaly detection
- intrusion detection system
- naive bayes
- feature space
- network traffic
- text classification
- random forest
- support vector
- feature subset
- unsupervised learning
- model selection
- combining multiple
- classification accuracy
- combining classifiers
- network traffic data
- learning algorithm
- machine learning
- network intrusions
- decision trees
- support vector machine
- data warehouse