Research on penetration testing based on machine learning

Yifan Liu


Supervised by Amir Javed; Moderated by Omer F Rana

The scope With the increase of data, the improvement of computing power and the emergence of new machine learning algorithms, modern technology based on machine learning has made remarkable achievements in the field of network security. Such as spam detection, equipment certification, industrial control system security, etc. Although these methods can improve the security of the system, it is particularly important to find system vulnerabilities and improve the security of the system itself. Penetration testing is to do this. This project will study the existing machine learning algorithm and its application in penetration testing, and develop a penetration testing tool for web applications.

The current state of the art -Reinforcement learning -Deep learning -Game theory

Final Report (04/11/2021) [Zip Archive]

Publication Form