Mahir Mohammed Sharif
Papers
1
Total Citations
3
H-Index
1
About
Mahir Mohammed Sharif is a leading researcher at the intersection of cybersecurity, artificial intelligence, and the Industrial Internet of Things (IIoT), with a particular focus on securing next-generation industrial systems. His work addresses critical challenges in Industry 5.0, especially the detection of cyber threats in highly imbalanced datasets—a common yet difficult problem in real-world industrial environments. In his highly cited 2025 paper, Sharif introduces a novel feature enhancement model combined with up-sampling techniques to improve attack classification accuracy, directly tackling the hyper-automation trends that define modern smart factories. This research has already garnered significant attention, accumulating citations that underscore its immediate relevance to both academia and industry. By developing AI-driven methods that can reliably identify rare but dangerous cyberattacks, Sharif is helping to build the foundational security infrastructure for the automated factories of the future. His contributions are essential reading for anyone working on resilient IIoT systems, adversarial machine learning, or the safe deployment of AI in critical infrastructure.
Research Focus
Key Achievements
Top Papers
- 1