Advanced Cryptography (AC)

Description

This course bridges the gap between Machine Learning (ML)and cybersecurity, focusing on how ML algorithms can be utilized to fortify cybersecurity measures and applications. We will cover the application of ML models to detect anomalies, predict attacks, and automate threat intelligence. Students will learn about the challenges and opportunities of applying ML in a cybersecurity context, including ethical considerations and the need for robust, secure ML models as there are many security applications which have large amount of data related to the system as well as adversarial actions. In the course, students will learn the theoretical concepts during the lectures as exploring different problem domains, gain hands-on experience to build up their skills by practicing on assignments, and finally demonstrate their knowledge and skills by participating in a final project to identify the type of machine learning algorithms that are useful for specific security applications and how to improve the defence against attacks to ultimately anticipate the potential attack variants that may rise in the future.