A two-stage stacked ensemble intrusion detection system using five base classifiers and MLP with optimal feature selection.
Earum MushtaqAneela ZameerAsifullah KhanPublished in: Microprocess. Microsystems (2022)
Keyphrases
- base classifiers
- intrusion detection system
- multi class
- ensemble methods
- feature selection
- ensemble learning
- intrusion detection
- ensemble classifier
- feature set
- naive bayes
- feature subset
- decision trees
- ensemble pruning
- random forest
- ensemble feature selection
- classifier ensemble
- anomaly detection
- distributed intrusion detection
- class labels
- combining classifiers
- training set
- text categorization
- text classification
- neural network
- classification accuracy
- cost sensitive
- prediction accuracy
- test data
- classifier combination
- feature extraction
- computer systems
- multiple classifier systems
- pruning method
- databases
- data sets
- feature space
- classification models
- training samples
- machine learning
- data mining
- pairwise
- knn
- machine learning methods
- benchmark datasets
- k nearest neighbor