Centralised vs decentralised anomaly detection: when local and imbalanced data are beneficial.
Mirko NardiLorenzo ValerioAndrea PassarellaPublished in: LIDTA@ECML/PKDD (2021)
Keyphrases
- anomaly detection
- imbalanced data
- intrusion detection
- linear regression
- class distribution
- detecting anomalies
- anomalous behavior
- ensemble methods
- random forest
- intrusion detection system
- feature selection
- support vector machine
- one class support vector machines
- class imbalance
- sampling methods
- decision trees
- neural network
- svm classifier
- classification models
- evolutionary algorithm
- machine learning
- text classification
- data sets
- machine learning methods
- base classifiers
- unsupervised learning
- least squares
- minority class
- computer vision
- genetic algorithm