INTRODUCTION & COURSE MAP

Welcome to the AI for Cybersecurity training, a project funded by CyBOK that provides active learning-based materials for students and lecturers to learn the topic.

This course aims to teach higher education students how to develop and use AI to detect cyber attacks. We use an active learning approach, which means students learn each topic through in-class discussions, hands-on activities, and so on. To get the most benefit from this course, students need to know at least some basics of Python programming.

In the beginning, before learning AI for Cybersecurity, students should learn AI, machine learning, and cybersecurity fundamental concepts. They must understand how machine learning works, the concepts of cybersecurity, the different types of cyber-attacks, and so forth. Therefore, we have also provided several links to videos, external documents (like websites), and in-class discussions for students to learn about AI and cybersecurity concepts. However, our main source for learning many of these topics is CyBOK knowledge areas and supplementary guides.

The idea is to first learn some basics of cyber security, cyber attacks, machine learning methods, and algorithms. In the next step, students will focus on three important cyber threats, which are email attacks, malware, and network attacks. They should learn more details about each threat, how cyber security experts can detect them, and finally, how we can develop a machine learning solution to detect that attack. So, for instance, students learn how attackers compromise a victim using phishing emails. They will then learn how cyber security experts and other users can detect a phishing email, and finally, learn how to develop a machine learning model to detect a phishing email. The students will learn this by watching some videos, having in-class discussions, searching and finding existing solutions and discussing them, generating a phishing email and using existing tools to detect them, and finally developing a machine learning model to detect phishing using Python in a lab environment.

The following is this course’s map. We recommend following these steps to teach and learn using AI for cybersecurity.

For more information about the project and the course materials, please get in touch with CyBOK or the Project Team.

© Crown Copyright, The National Cyber Security Centre 2024. This information is licensed under the Open Government Licence v3.0. To view this licence, visit https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.
When you use this information under the Open Government Licence, you should include the following attribution: © Crown Copyright, The National Cyber Security Centre 2024, licensed under the Open Government Licence: https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.