On the Evaluation of Spiking Neural Network Configurations for Network Intrusion Detection

ArXi:2606.01442v1 Announce Type: cross Network intrusion detection is a core component of modern cybersecurity infrastructure, yet the deep learning models that dominate the field are computationally demanding, motivating interest in lightweight alternatives suited to edge and neuromorphic deployment. Spiking Neural Networks (SNNs) are. therefore. a natural candidate, but their design space, spanning the choice of neuron model and spike encoding scheme, remains poorly characterized for intrusion detection.