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02/04/2026

1 min read By Mustafa Aljumaily, Hyder Abed, Salam Alyassri

AI-Driven Threat Intelligence for IoT Networks: Leveraging Machine Learning for Enhanced Intrusion Detection

As Internet of Things (IoT) devices continue to spread, they also create many new entry points for cyberattacks. Traditional security methods struggle to keep up, which makes smarter and more adaptive defenses necessary. This paper introduces an Artificia

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02/04/2026

1 min read By Mustafa Aljumaily, Hayder Abd, Elaf Majeed

Enhancing User and Entity Behavior Analytics in SIEM Systems Using AI-Powered Anomaly Detection: A Data-Driven Simulation Approach

The growing sophistication of cyber threats exposes the limits of signature-based detection in Security Information and Event Management (SIEM) systems. User and Entity Behavior Analytics (UEBA) advances SIEM by enabling behavior-based anomaly detection,

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02/04/2026

1 min read By Mustafa Aljumaily, Sherwan Abdullah, Ahmed Abd Alhasan

A Hybrid Intrusion Detection Framework for CyberPhysical Security in Smart Home/Smart City IoT Systems

The rapid expansion of smart home and smart city technologies has introduced a complex array of interconnected Internet of Things (IoT) devices, exposing both cyber and physical infrastructures to a growing spectrum of security threats. Traditional cybers

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02/04/2026

1 min read By Mustafa Aljumaily, Sherwan Abdullah

An AI-Driven Framework for Adaptive eSystems in Harsh Environments: A Case Study from Oilfield IoT Applications

Harsh industrial environments such as oilfields present unique challenges to electronic systems, including extreme temperatures, limited connectivity, power constraints, and operational unpredictability. Traditional Internet of Things (IoT) deployments of

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02/04/2026

1 min read By Mustafa Aljumaily, Hyder Abed

AI-Driven Digital Twin Frameworks for Predictive Monitoring of IoT Networks in Harsh Environments

Keeping IoT networks running reliably in harsh environments is still a tough problem. Sensors wear out, communication links are unreliable, and maintenance quickly becomes expensive. These issues make traditional monitoring approaches fragile and slow to

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