Congratulations Esmond Awortwe

Esmond Awortwe is a graduating MPhil student from the Telecommunication Engineering Department at KNUST, with research interests spanning the Internet of Things (IoT), Machine Learning, Security Vulnerabilities and Communication Networks in general.

Her final research aimed to enhance the security testing of IOT devices by integrating machine learning, specifically Reinforcement Learning (RL) with Proximal Policy Optimization (PPO), into the fuzzing process.  The primary objectives were to improve the code coverage, reduce the time to discover vulnerabilities, increase the number of bugs, minimise false positives, and optimise overall efficiency in the fuzzing process.  Her findings underscore the potential of RL-enhanced fuzzing as a powerful tool for IOT security testing, providing a more adaptive and effective way to identify vulnerabilities in complex heterogenous IOT ecosystems.  The ability of the PPO-based model to dynamically adjust fuzzing strategies based on real-time feedback allows for a more thorough exploration of code paths, leading to the discovery of previously undetected vulnerabilities.

Esmond credits and expresses her gratitude to the KNUST Engineering Education Project (KEEP) for its pivotal role in her academic journey, acknowledging the financial support and encouragement provided by the KEEP staff and management.

She would like to thank her supervisor, Dr Justice Owusu Agyemang, for the timely guidance and support she has received in her work.

She plans to continue advancing her research in IOT security vulnerabilities, applying machine learning, specifically RL, in the fuzzing process, and sharing her expertise through teaching and working with telco industries.