Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware.
Mikhail ZolotukhinTimo HämäläinenPublished in: GLOBECOM Workshops (2013)
Keyphrases
- support vector machine
- genetic algorithm
- classification method
- support vector
- svm classifier
- feature vectors
- support vector machine svm
- training set
- svm classification
- feature selection
- generalization ability
- classification algorithm
- multi class
- false positives
- machine learning
- binary decision tree
- decision trees
- k nearest neighbor
- kernel function
- high classification accuracy
- multi class support vector machines
- support vector machine classifier
- neyman pearson
- detection method
- supervised learning
- object detection
- pattern recognition
- malware detection
- small sample
- digital mammograms
- soft margin
- reverse engineering
- model selection
- pattern classification
- classification accuracy
- detection algorithm
- image classification
- neural network
- sequential minimal optimization
- robust detection
- multiclass classification
- feature extraction