Automated System-Level Anomaly Detection and Classification Using Modified Random Forest.
Nana Kwame GyamfiDainius CeponisNikolaj GoraninPublished in: ICAIC (2022)
Keyphrases
- anomaly detection
- random forest
- decision trees
- fold cross validation
- feature set
- intrusion detection
- random forests
- decision tree learning algorithms
- detecting anomalies
- pattern recognition
- anomalous behavior
- unsupervised learning
- network anomaly detection
- intrusion detection system
- one class support vector machines
- feature extraction
- machine learning
- network traffic
- classification accuracy
- network intrusion detection
- support vector
- ensemble methods
- negative selection algorithm
- detect anomalies
- ensemble classifier
- machine learning methods
- benchmark datasets
- image classification
- support vector machine
- feature selection
- ensemble learning
- base classifiers
- multi label
- model selection
- training set
- feature space