Innovative Research Award
Ahmed Burhan Mohammed — University of Kirkuk, Iraq
Ahmed Burhan Mohammed is a researcher affiliated with the University of Kirkuk in Iraq whose scholarly profile is associated with Internet of Things security and intelligent intrusion detection. His research record includes studies addressing machine-learning-based cybersecurity, intrusion detection datasets, and intelligent protection of connected systems. The profile records 17 documents, 143 citations, and an h-index of 7, indicating a developing research trajectory in a technically significant area of cybersecurity. His published work also demonstrates engagement with applied computational methods for securing interconnected and emerging communication environments. [1][3]
Abstract
Ahmed Burhan Mohammed, affiliated with the University of Kirkuk, Iraq, conducts research primarily in IoT Security and intelligent intrusion detection. His scholarly work addresses cybersecurity challenges affecting connected and autonomous communication environments, with emphasis on machine-learning methods, datasets, and practical detection frameworks. His research includes investigations of intelligent intrusion detection for Internet of Things and unmanned aerial vehicle communications, together with recent work exploring KAN-based frameworks and SMOTE for improving real-time detection. His publication record comprises 17 documents, receiving 143 citations and an h-index of 7. These indicators, combined with his applied research orientation, provide evidence of continued engagement with contemporary cybersecurity problems and technologies. [1][3]
Keywords
IoT Security; Intrusion Detection; Machine Learning; Cybersecurity; Intelligent Systems; Internet of Things; UAV Communications; Network Security; SMOTE; KAN-Based Frameworks; Anomaly Detection.
Introduction
The expansion of connected devices has increased the need for reliable cybersecurity mechanisms capable of identifying malicious activity in complex network environments. Mohammed’s research addresses this challenge through intelligent intrusion detection, dataset investigation, and machine-learning-oriented approaches. His work is relevant to IoT and emerging communication systems where timely threat identification is important. [1][3]
Research Profile
Mohammed’s research profile is centered on IoT Security, with particular relevance to intelligent intrusion detection and secure communication. His publication activity indicates an applied computational perspective, combining cybersecurity requirements with data-driven analytical techniques. The documented record of 17 publications, 143 citations, and an h-index of 7 reflects measurable scholarly activity within this research domain. [1][3]
Research Contributions
A notable contribution of Mohammed’s research is its focus on improving intelligent intrusion detection across emerging network environments. His work considers dataset characteristics and machine-learning frameworks for cybersecurity applications, including UAV communication systems and IoT networks. Recent research involving KAN-based approaches and SMOTE further reflects attention to improving real-time detection capabilities. [1][3]
Publications
Mohammed’s documented publications address cybersecurity and intelligent systems through complementary research directions. These include real-time IoT intrusion detection using KAN-based frameworks with SMOTE, investigation of datasets for intelligent intrusion detection in intra- and inter-UAV communications, and interdisciplinary engineering research involving multi-objective optimization. Together, these publications illustrate breadth across computational security and applied engineering research. [1][2][3]
Research Impact
The research has potential relevance to cybersecurity research because intelligent intrusion detection is increasingly important for connected devices and autonomous communication environments. The citation record of 143 and h-index of 7 provides an established measure of scholarly visibility. The work’s focus on practical detection and datasets supports continued investigation into secure intelligent networks. [1][3]
Award Suitability
Ahmed Burhan Mohammed demonstrates suitability for consideration for an Innovative Research Award through research focused on contemporary cybersecurity challenges and intelligent intrusion detection. His work combines applied security problems with computational approaches, while his publication and citation record demonstrates sustained scholarly activity. The alignment between IoT security research and technological innovation provides a relevant basis for recognition. [1][3]
Conclusion
Ahmed Burhan Mohammed’s research reflects sustained engagement with IoT security, intelligent intrusion detection, and data-driven cybersecurity methods. His publications address emerging communication environments and practical detection challenges, supported by measurable scholarly impact. The combination of technical focus, applied research orientation, and continued publication activity supports consideration for the Innovative Research Award. [1][3]
External Links
References
- Enhancing real-time IoT intrusion detection using KAN-based frameworks with SMOTE. (2026). Computer Networks. Elsevier.
https://www.sciencedirect.com/science/article/abs/pii/S1084804526000366?via%3Dihub
- Combustion and Emission Analysis of NH3-Diesel Dual-Fuel Engines Using Multi-Objective Response Surface Optimization. (2025). Atmosphere, 16(9), 1032. MDPI.
https://www.mdpi.com/2073-4433/16/9/1032
- Investigation on datasets toward intelligent intrusion detection systems for Intra and inter-UAVs communication systems. (2024). Computers & Security. Elsevier.
https://www.sciencedirect.com/science/article/abs/pii/S0167404824005212?via%3Dihub
- Elsevier. (n.d.). Scopus author details: Ahmed Burhan Mohammed, Author ID 57686887900. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57686887900