Leveraging Homeostatic Plasticity to Enable Anomaly Detection in Spiking Neural Networks.
Rawan M. A. NawaisehFabrizio De VitaEnrico CatalfamoDario BruneoPublished in: SMARTCOMP (2024)
Keyphrases
- anomaly detection
- spiking neural networks
- biologically inspired
- learning rules
- biologically plausible
- intrusion detection
- synaptic plasticity
- artificial neural networks
- feed forward
- detecting anomalies
- spiking neurons
- anomalous behavior
- neural network
- network intrusion detection
- intrusion detection system
- motor control
- network traffic
- one class support vector machines
- network anomaly detection
- training algorithm
- unsupervised learning
- detect anomalies
- negative selection algorithm
- input data
- normal behavior
- back propagation
- data sets