Anomaly Detection Using SVM as Classifier and Decision Tree for Optimizing Feature Vectors.
Elham SerkaniHossein Gharaee GarakaniNaser MohammadzadehPublished in: ISC Int. J. Inf. Secur. (2019)
Keyphrases
- anomaly detection
- feature vectors
- decision trees
- svm classifier
- support vector machine
- train a support vector machine
- feature space
- feature set
- intrusion detection
- training data
- decision forest
- decision tree classifiers
- detecting anomalies
- anomalous behavior
- support vector
- network intrusion detection
- support vector machine svm
- network traffic
- feature extraction
- training set
- classification algorithm
- intrusion detection system
- machine learning
- bayesian classifiers
- network anomaly detection
- unsupervised anomaly detection
- naive bayes
- detecting anomalous
- one class support vector machines
- similarity measure
- feature selection
- negative selection algorithm
- detect anomalies
- unsupervised learning
- cumulative sum
- network security
- multi class
- machine learning algorithms
- data sets
- classification accuracy
- high dimensional
- genetic algorithm
- knn
- ensemble methods
- principal component analysis
- text mining
- kernel function