Jawhara Aljabri
Papers
1
Total Citations
3
H-Index
1
About
Jawhara Aljabri is a rising researcher in cybersecurity and artificial intelligence, with a focus on safeguarding the Industrial Internet of Things (IIoT). Her work addresses critical challenges in Industry 5.0, particularly the detection and classification of cyber threats in imbalanced datasets—a common yet difficult problem in real-world industrial environments. In her most cited paper, "Feature enhancement model with up sampling based cyber threat attack detection and classification on imbalanced dataset in Industrial Internet of Things" (2025, 3 citations), she proposes an innovative AI-driven approach that combines feature enhancement and up-sampling techniques to improve threat detection accuracy. This work contributes to the broader goal of hyper-automation in industrial communication, where reliable and secure AI models are essential. Though early in her career, Aljabri’s research is already gaining attention for its practical relevance to cybersecurity in smart manufacturing and critical infrastructure. Her work sits at the intersection of machine learning, data imbalance resolution, and industrial security, offering promising solutions for more resilient and automated industrial systems.
Research Focus
Key Achievements
Top Papers
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