Annotation: The paper investigates the problem of detecting network anomalies in the processing of data streams in industrial systems. The network anomaly is understood as the malicious signature and the current context: the network environment and topology, routing parameters and node characteristics. As a result of the study, it was proposed to use a neocortex model that supports the memory mechanism to detect network anomalies.

Keywords: hierarchical temporary memory, artificial intelligence, contextual anomalies, machine learning, neocortex, industrial internet of thighs, network traffic, HTM.