A multiple spiking neural network architecture based on fuzzy intervals for anomaly detection: a case study of rail defects.
Wassamon PhusakulkajornJurjen HendriksJan MoraalRolf P. B. J. DollevoetZili LiAlfredo NúñezPublished in: FUZZ-IEEE (2022)
Keyphrases
- anomaly detection
- intrusion detection
- detecting anomalies
- anomalous behavior
- network traffic
- intrusion detection system
- behavior analysis
- detecting anomalous
- computer security
- network intrusion detection
- unsupervised anomaly detection
- network security
- malware detection
- detect anomalies
- fuzzy logic
- network anomaly detection
- negative selection algorithm
- fuzzy systems
- unsupervised learning
- one class support vector machines
- data sets
- reinforcement learning
- machine learning