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Nonye Peter Awurum

4 papers indexed

zenodoJournal article2026-07-27

Reducing False Positives in AI-Based Intrusion Detection Systems Using Hybrid Artificial Intelligence for Oil and Gas Critical Infrastructure

Nonye Peter Awurum

Abstract: The increasing frequency and sophistication of cyberattacks targeting critical infrastructure have accelerated the adoption of Artificial Intelligence (AI)-based Intrusion Detection Systems (IDSs) for real-time cyber threat detection. Although machine learning and deep…

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zenodoJournal article2026-07-27

An AI-Powered Cybersecurity Framework for Real-Time Threat Detection and Resilience in Oil and Gas Critical Infrastructure

Nonye Peter Awurum

Abstract: The rapid digital transformation of the oil and gas industry has accelerated the convergence of Information Technology (IT) and Operational Technology (OT), enabling enhanced operational efficiency, predictive maintenance, and remote asset management. While these techno…

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zenodoJournal article2026-07-27

Performance Evaluation of Machine Learning and Deep Learning Models for Real-Time Cyberattack Detection in Oil and Gas Networks

Nonye Peter Awurum

Abstract: The rapid digital transformation of the oil and gas industry has significantly improved operational efficiency through the integration of Information Technology (IT) and Operational Technology (OT) systems. However, this increased connectivity has also expanded the cybe…

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zenodoJournal article2026-07-27

Hybrid Ensemble Learning for Real-Time Intrusion Detection in Critical Infrastructure Environments.

Nonye Peter Awurum

Abstract: The increasing digitization of critical infrastructure environments has significantly enhanced operational efficiency while simultaneously exposing industrial systems to sophisticated cyber threats. Critical sectors such as oil and gas, energy, transportation, and manuf…

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