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

Abstract

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.