Gradient Boosting Feature Selection With Machine Learning Classifiers for Intrusion Detection on Power Grids.
Darshana UpadhyayJaume ManeroMarzia ZamanSrinivas SampalliPublished in: IEEE Trans. Netw. Serv. Manag. (2021)
Keyphrases
- feature selection
- power grids
- intrusion detection
- machine learning
- power grid
- cyber security
- feature set
- text classification
- support vector
- telecommunication systems
- single feature
- intrusion detection system
- machine learning algorithms
- support vector machine
- feature subset
- naive bayes
- decision trees
- anomaly detection
- malicious code detection
- feature ranking
- critical infrastructure
- data mining
- meta learning
- classification accuracy
- machine learning methods
- network security
- network traffic
- wind power
- information security
- svm classifier
- training data
- smart grid
- model selection
- active learning
- multi class
- dimensionality reduction
- feature space
- short term
- data mining techniques
- training set
- unsupervised learning
- data analysis
- data processing
- databases
- ensemble learning
- high dimensional
- cross validation