Supervisor: Associate Professor Dan Kim
This project will investigate state-of-the-art techniques in penetration testing. The candidate will work on 1) literature reviews on autonomous and automated pen-testing, 2) reviews on reinforcement learning and its advances, 3) develop an improved autonomous and automated pen-testing using an improved reinforcement learning, and 4) implement the proposed approach and evaluate the performance of the proposed approach.
Selection criteria:
Your application will be assessed on a competitive basis.
We take into account your:
A working knowledge of computer science and cybersecurity would be of benefit to someone working on this project.
You will demonstrate academic achievement in the field/s of cybersecurity and the potential for scholastic success.
A background or knowledge of computer science, cybersecurity, and pen testing is highly desirable.
You're eligible if you meet the entry requirements for a higher degree by research.