Muhammad Ahmad

Muhammad Ahmad is a researcher in the Department of Electrical Engineering at the College of STEM Engineering & Computing Sciences, affiliated with National University of Sciences and Technology Pakistan. His work focuses on cybersecurity challenges in Internet of Things (IoT) environments, particularly leveraging supervised machine learning techniques for intrusion detection.

His research utilizes the UNSW-NB15 dataset and explores feature clusters like Flow, MQTT, and TCP to address over-fitting, dimensionality, and data imbalance. He collaborates with institutions such as State University of New York at Fredonia and Arkansas Tech University on security solutions for low-power IoT devices.

This work was published in the Eurasip Journal on Wireless Communications and Networking (2021), achieving high accuracy rates in binary and multi-class classification using Random Forest algorithms.