A real-time network based anomaly detection in industrial control systems-Reference-Cited by-同舟云学术

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A real-time network based anomaly detection in industrial control systems

Published:2024-07 Issue: Volume:45 Page:100676
ISSN:1874-5482
Container-title:International Journal of Critical Infrastructure Protection
language:en
Short-container-title:International Journal of Critical Infrastructure Protection

Author:

Zare Faeze,Mahmoudi-Nasr Payam^ORCID,Yousefpour Rohollah

Publisher

Elsevier BV

Reference25 articles.

1. Evolutionary deep belief network for cyber-attack detection in industrial automation and control system;Lu;IEEe Trans. Industr. Inform.,2021

2. ICS-CERT, "Threat landscape for industrial automation systems," https://ics-cert.kaspersky.com/publications/reports/2021/03/25/threat-landscape-for-industrial-automation-systems-statistics-for-h2-2020/, 25.03.2021 2021.

3. A survey of physics-based attack detection in cyber-physical systems;Giraldo;ACM Comput. Surv. (CSUR),2018

4. DAICS: a deep learning solution for anomaly detection in industrial control systems;Abdelaty;IEEE Trans. Emerg. Top. Comput.,2021

5. MODLSTM: a Method to Recognize DoS Attacks on Modbus/TCP;Zhang,2022

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