Fortunatus A. Wulnye is a graduating MPhil student from the Telecommunication Engineering Department at KNUST, with research interests spanning Network Security, the Internet of Things (IoT), Machine Learning in Agriculture, Automation, and Communication Networks.
His final research focused on evaluating the vulnerability of IoT Network Intrusion Detection Systems (NIDS) to data poisoning attacks using advanced machine learning models. Through rigorous assessment of various algorithms on real-world datasets, his work revealed the susceptibility of NIDS to data poisoning and highlighted the necessity for more robust security protocols. These findings underscore the vital role of machine learning in enhancing the resilience of Intrusion Detection Systems (IDS) against evolving threats within IoT ecosystems.
Fortunatus credits and expresses his gratitude to the KNUST Engineering Education Project (KEEP) for its pivotal role in his academic journey, acknowledging the financial support and encouragement provided by the KEEP staff and management. Looking ahead, he plans to continue advancing his research in securing communication networks, applying machine learning in Intrusion Detection and Prevention Systems, and sharing his expertise through teaching.