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Published in: Automatic Control and Computer Sciences 8/2023

01-12-2023

Cyberattack Detection in the Industrial Internet of Things Based on the Computation Model of Hierarchical Temporal Memory

Authors: V. M. Krundyshev, G. A. Markov, M. O. Kalinin, P. V. Semyanov, A. G. Busygin

Published in: Automatic Control and Computer Sciences | Issue 8/2023

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Abstract

This study considers the problem of detecting network anomalies caused by computer attacks in the networks of the industrial Internet of things. To detect anomalies, a new method is proposed, built using a hierarchical temporal memory (HTM) computation model based on the neocortex model. An experimental study of the developed method of detecting computer attacks based on the HTM model showed the superiority of the developed solution over the LSTM analog. The developed prototype of the anomaly detection system provides continuous training on unlabeled data sets in real time, takes into account the current network context, and applies the accumulated experience by supporting the memory mechanism.
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Metadata
Title
Cyberattack Detection in the Industrial Internet of Things Based on the Computation Model of Hierarchical Temporal Memory
Authors
V. M. Krundyshev
G. A. Markov
M. O. Kalinin
P. V. Semyanov
A. G. Busygin
Publication date
01-12-2023
Publisher
Pleiades Publishing
Published in
Automatic Control and Computer Sciences / Issue 8/2023
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI
https://doi.org/10.3103/S0146411623080114

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