Autoencoder with Adaptive Loss Function for Supervised Anomaly Detection.
Yasuhiro KanishimaTakashi SudoHiroyuki YanagihashiPublished in: KES (2022)
Keyphrases
- anomaly detection
- loss function
- intrusion detection
- unsupervised learning
- pairwise
- detecting anomalies
- network intrusion detection
- support vector
- anomalous behavior
- intrusion detection system
- supervised learning
- network anomaly detection
- network traffic
- detect anomalies
- one class support vector machines
- risk minimization
- detecting anomalous
- boosting framework
- learning algorithm
- negative selection algorithm
- reproducing kernel hilbert space
- feature selection
- machine learning
- network security
- kernel methods
- semi supervised
- information extraction
- k means
- feature space
- reinforcement learning
- connectionist systems