Handbook

This course covers theories and their practical implementation of deep learning for cyber security solutions. Deep learning is a subset of machine learning that involves the use of artificial neural networks to learn and make predictions based on large data sources. In the context of cyber security, deep learning models can be used to analyse vast amounts of data to build offensive and defensive strategies, such as automated penetration testing, intrusion discovery, vulnerability and malware detection in real-time. This can help organisations to understand how cyber threats would occur, detect and prevent them before they cause significant damage and achieve cyber resilience. Students learn discriminative and generative deep learning algorithms, Autoencoders, and convolution networks for various red-blue teaming scenarios from the industry perspective.