Application of a Neocortex Model to Identify Contextual Anomalies in the Industrial Internet of Things Network Traffic.

This paper examines the problem of identifying network anomalies when processing data streams in industrial systems. A network anomaly refers to a malicious signature and the current context: network environment and topology, routing parameters, and node characteristics. As a result of the study, it is proposed to use a neocortex model that supports the memory mechanism to detect network anomalies. [ABSTRACT FROM AUTHOR]