Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic.
Jayro Santiago-PazDeni Torres RománAngel Figueroa-YpiñaJesús Argáez-XoolPublished in: Entropy (2015)
Keyphrases
- network traffic
- anomaly detection
- support vector
- support vector machine svm
- svm classification
- support vector machine
- detecting anomalous
- intrusion detection
- detect anomalies
- kernel function
- feature space
- histogram intersection kernel
- svm classifier
- classification algorithm
- kernel methods
- traffic patterns
- rbf kernel
- feature vectors
- kernel machines
- intrusion detection system
- normal traffic
- feature selection
- network intrusion detection
- multiple kernel learning
- network security
- standard svm
- traffic data
- pattern recognition
- unsupervised learning
- network attacks
- network bandwidth
- training set
- network intrusion
- network traffic data
- decision trees
- network monitoring
- kernel support vector machines
- long range dependence
- internet traffic
- network resources
- text classification
- supervised learning
- multi class
- information systems
- learning algorithm
- knn
- object recognition
- feature extraction
- machine learning