Abstract
We introduce a discrete-event artificial neural network structure inspired by biological neural networks. It includes dynamic components and has variable structure. The network’s topology and its dynamic components are modifiable and trainable for different applications. Such adaptation in the network’s parameters, structure, and dynamic components makes it easier to adapt to varying behaviors due to the problem’s structure than other types of networks. We demonstrate that this type of network structure can detect random changes in packet arrival rates in computer network traffic with possible applications in cyber security.
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