Naseem Khan
Papers
1
Total Citations
3
H-Index
1
About
Naseem Khan is an emerging researcher at the intersection of cybersecurity, artificial intelligence, and next-generation industrial systems. His work focuses primarily on explainable AI (XAI), intrusion detection systems, and the evolving security challenges presented by Industry 5.0 environments. In his most notable contribution, Khan explores how AI-driven intrusion detection can be made transparent and interpretable within complex industrial ecosystems — a critical challenge as manufacturing environments increasingly integrate IoT devices, collaborative robots, and augmented reality technologies. His 2024 overview comprehensively maps the existing literature on XAI-based security solutions, identifies key challenges in protecting hyper-connected Industry 5.0 infrastructures, and proposes promising directions for future research. Though early in his publishing trajectory with 3 citations to date, his work addresses a timely and rapidly growing field where the demand for trustworthy, human-centered AI security solutions is accelerating. Khan's research is particularly valuable for practitioners and scholars seeking to bridge the gap between advanced machine learning techniques and real-world industrial cybersecurity deployment, positioning him as a researcher to watch as Industry 5.0 adoption continues to expand globally.
Research Focus
Key Achievements
Top Papers
- 1