dLSTM: a new approach for anomaly detection using deep learning with delayed prediction.
Shigeru MayaKen UenoTakeichiro NishikawaPublished in: Int. J. Data Sci. Anal. (2019)
Keyphrases
- intrusion detection system
- anomaly detection
- deep learning
- unsupervised learning
- intrusion detection
- network traffic
- network intrusion detection
- detecting anomalies
- anomalous behavior
- unsupervised feature learning
- machine learning
- mental models
- network anomaly detection
- supervised learning
- weakly supervised
- model selection
- one class support vector machines
- semi supervised
- normal behavior
- negative selection algorithm
- pattern recognition
- computer vision
- detect anomalies
- learning algorithm
- information retrieval