SNIPER: Few-shot Learning for Anomaly Detection to Minimize False-negative Rate with Ensured True-positive Rate.
Yuma KoizumiShin MurataNoboru HaradaShoichiro SaitoHisashi UematsuPublished in: ICASSP (2019)
Keyphrases
- anomaly detection
- false positive rate
- connectionist systems
- learning process
- true positive rate
- false negative rate
- unsupervised learning
- network intrusion detection
- anomalous behavior
- reinforcement learning
- supervised learning
- intrusion detection
- detecting anomalies
- learning algorithm
- detection rate
- network traffic
- network security
- low false positive rate
- intrusion detection system
- active learning
- pattern recognition
- network anomaly detection
- detecting anomalous
- computer vision