Network Intrusion Detection Based on Conditional Wasserstein Generative Adversarial Network and Cost-Sensitive Stacked Autoencoder.
Guoling ZhangXiaodan WangRui LiYafei SongJiaxing HeJie LaiPublished in: IEEE Access (2020)
Keyphrases
- cost sensitive
- network intrusion detection
- fraud detection
- network intrusion
- network anomaly detection
- network attacks
- network traffic
- misclassification costs
- multi class
- cost sensitive learning
- intrusion detection
- anomaly detection
- naive bayes
- class distribution
- cost sensitive classification
- active learning
- class imbalance
- intrusion detection system
- computer networks
- support vector machine
- social network analysis
- network security
- training set
- computer systems
- training data
- classification accuracy
- boosting algorithms
- data mining
- unsupervised learning