CSE-IDS: Using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems.
Neha GuptaVinita JindalPunam BediPublished in: Comput. Secur. (2022)
Keyphrases
- cost sensitive
- class imbalance
- intrusion detection system
- intrusion detection
- cost sensitive learning
- misclassification costs
- class distribution
- multi class
- anomaly detection
- boosting algorithms
- learning algorithm
- cost sensitive boosting
- fraud detection
- active learning
- support vector machine
- data sets
- benchmark datasets
- data mining techniques
- base classifiers
- pattern recognition
- small number
- training data
- imbalanced data