Supervisor

Dr Saeed Rehman
Rehman, Saeed (Dr)
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Project description

This project would investigate the generative attack model on wireless networks. Generative adversarial networks (GAN) consists of two deep neural networks, generator and discriminator. The generator learns from the output of the discriminator and gets better at faking the data with time. The motivation of the research is to investigate and design a generative attack model that can generate fake data capable of fooling the machine learning-based IDS. The proposed attack model would provide an opportunity for studying attacks that can bypass current advance machine learning-based IDS.

Assumed knowledge

Understanding of Network attacks, Machine learning algorithms, Programming (Matlab or Python)


Note: You need to register interest in projects from different supervisors (not a number of projects with the one supervisor).
You must also contact each supervisor directly to discuss both the project details and your suitability to undertake the project.