Network Anomaly Classification by Support Vector Classifiers Ensemble and Non-linear Projection Techniques.
Eduardo de la Hoz CorreaAndrés OrtizJulio Ortega LoperaEmiro de la Hoz FrancoPublished in: HAIS (2013)
Keyphrases
- network traffic
- final classification
- pattern recognition
- classification accuracy
- neural network
- benchmark datasets
- image classification
- support vector machine
- training set
- regression problems
- anomaly detection
- automatic classification
- support vector machine svm
- ensemble classifier
- classifier ensemble
- unsupervised learning
- feature selection
- pattern classification
- classification method
- classification systems
- classification scheme
- machine learning
- peer to peer
- supervised learning
- concept drifting data streams
- abnormal events
- feature extraction
- multiple classifiers
- classifier combination
- imbalanced data
- support vector
- feature vectors
- complex networks
- text classification
- class imbalance
- intrusion detection
- generalization ability
- classification algorithm
- computer networks
- network structure