A Supervised Rare Anomaly Detection Technique via Cooperative Co-evolution-Based Feature Selection Using Benchmark UNSW_NB15 Dataset.
A. N. M. Bazlur RashidMohiuddin AhmedSheikh Rabiul IslamPublished in: UbiSec (2021)
Keyphrases
- anomaly detection
- feature selection
- cooperative
- unsupervised learning
- fold cross validation
- naive bayes
- feature set
- intrusion detection
- text categorization
- detecting anomalies
- anomalous behavior
- network intrusion detection
- machine learning
- network traffic
- dimensionality reduction
- text classification
- novelty detection
- unsupervised anomaly detection
- detecting anomalous
- one class support vector machines
- computer security
- behavior analysis
- decision trees
- intrusion detection system
- sparse pca
- multi class
- classification accuracy
- supervised learning
- negative selection algorithm
- detect anomalies
- malware detection
- semi supervised
- network anomaly detection
- active learning
- learning algorithm
- feature space
- object recognition
- feature extraction
- training data
- genetic algorithm
- model selection
- real world
- network security