Identification of Malware Mimicry Attacks Using Process Escalating Visualization

Amer, Eslam

doi:10.1109/imsa58542.2023.10217436

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2024

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Cited by 3 publications

References 29 publications

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From Black Boxes to Transparent Insights: Enhancing Industrial Control Systems Anomaly Detection with Deep Autoencoder Models

Amer,

Al-rimy,

El-Sappagh

et al. 2024

2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC)

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From Black Boxes to Transparent Insights: Enhancing Industrial Control Systems Anomaly Detection with Deep Autoencoder Models

Amer,

Al-rimy,

El-Sappagh

et al. 2024

2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC)

View full text Add to dashboard Cite

Evaluating Machine Learning Techniques for ICS Security: Insights from Dataset Limitations and Classifier Performance

Amer,

Elboghdadly

2024

2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC)

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Infrastructure and Tools for Testing the Vulnerability of Control Systems to Cyberattacks: A Coal Mine Industrial Facility Case

Plamowski,

Chaber,

Ławryńczuk

et al. 2024

Applied Sciences

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Testing the vulnerability of information systems to cyberattacks is essential to ensure the operational security of organizations and industrial processes. In particular, it is essential to ensure the resilience of industrial processes, as a possible cyberattack can lead to process malfunctions and even process shutdowns, which can lead to substantial economic losses. The possibility of various attacks, e.g., ransomware, phishing, or advanced persistent threats (APTs), requires the evaluation of the effectiveness of cyberattack detection and incident response mechanisms. In industry, it is often impossible to carry out this type of test without risking system disruption, making it difficult to assess the true effectiveness of security features. This article discusses the issues concerned with testing the cyber resilience of a system operating in a real coal mine. First, this work briefly presents the hardware and software architecture used in the coal mine. Secondly, it describes the problem of replicating a real system in the laboratory and the necessary tools and methods used to implement a resilient system architecture. Finally, the scenarios of cyberattacks are detailed, and the obtained results are discussed.

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Identification of Malware Mimicry Attacks Using Process Escalating Visualization

Cited by 3 publications

References 29 publications

From Black Boxes to Transparent Insights: Enhancing Industrial Control Systems Anomaly Detection with Deep Autoencoder Models

From Black Boxes to Transparent Insights: Enhancing Industrial Control Systems Anomaly Detection with Deep Autoencoder Models

Evaluating Machine Learning Techniques for ICS Security: Insights from Dataset Limitations and Classifier Performance

Infrastructure and Tools for Testing the Vulnerability of Control Systems to Cyberattacks: A Coal Mine Industrial Facility Case

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