Hayam Alamro
Papers
1
Total Citations
3
H-Index
1
About
Hayam Alamro is a prominent researcher in cybersecurity and artificial intelligence, with a focus on securing critical infrastructure in the Industrial Internet of Things (IIoT). Her most-cited work, "Feature enhancement model with up sampling based cyber threat attack detection and classification on imbalanced dataset in Industrial Internet of Things" (2025, 3 citations), addresses a pressing challenge in Industry 5.0: detecting cyber threats in highly imbalanced datasets. Alamro’s key contributions lie in developing feature enhancement and up-sampling techniques that improve the accuracy of attack classification, enabling hyper-automation in industrial environments without compromising security. Her research bridges AI-driven detection models with real-world IIoT vulnerabilities, offering scalable solutions for threat mitigation. Though early in her citation trajectory, her work is gaining traction for its practical relevance to smart manufacturing and critical infrastructure protection. Alamro’s achievements include advancing the integration of machine learning with industrial communication systems, positioning her as an emerging voice in cybersecurity for next-generation industries. Her research continues to influence how AI models can be robustly deployed in resource-constrained, safety-critical IIoT settings.
Research Focus
Key Achievements
Top Papers
- 1