An Approach to Feature Selection in Intrusion Detection Systems Using Machine Learning Algorithms.
G. KavithaN. M. ElangoPublished in: Int. J. e Collab. (2020)
Keyphrases
- machine learning algorithms
- intrusion detection system
- feature selection
- intrusion detection
- machine learning
- input features
- network security
- benchmark data sets
- anomaly detection
- learning algorithm
- decision trees
- computer networks
- network traffic
- statistical machine learning
- learning problems
- network intrusion detection
- computer security
- machine learning methods
- intrusion prevention
- cyber security
- information gain
- distributed intrusion detection
- attack detection
- network intrusion detection systems
- learning tasks
- text categorization
- machine learning models
- computer systems
- naive bayes
- feature extraction
- data mining techniques
- machine learning approaches
- alert correlation
- feature space
- classification accuracy
- dimensionality reduction
- feature subset
- model selection
- feature set
- multi class
- support vector machine
- text classification
- unsupervised learning
- support vector
- data mining
- standard machine learning algorithms
- misuse detection
- neural network
- learning models
- classification models
- malicious activities
- reinforcement learning
- selected features
- machine learning and data mining algorithms
- information security