Courses / Modules / COMP6BBB Cyber Security and Machine Learning

Cyber Security and Machine Learning

When you'll study it: Semester 2
CATS points: 15
ECTS points: 7.5
Level: Level 7
Module lead: Boojoong Kang
Academic year: 2025-26

Module overview

This module covers two aspects of a pivotal intersection: applying security to defend machine learning and leveraging machine learning to enhance security. The aims at a high level are to: - Investigate security issues around machine learning systems - Review a variety of defence mechanisms for machine learning systems - Explore the use of machine learning in cyber security

Linked modules

Pre-requisites: COMP3222 or COMP3223 or COMP6245 or COMP6246

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Cyber threats to machine learning systems
Machine learning based cyber security applications
Machine learning based cyber threats
Defence mechanisms for machine learning systems

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

Evaluate security of machine learning systems
Apply machine learning approaches to the solution of complex cyber security problems

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

Design secure machine learning systems
Design machine learning based cyber security applications

Learning and Teaching

Teaching and learning methods

Lectures will be given to introduce each concept. The lectures will indicate wider reading from the literature to consolidate and deepen the understand the material. Tutorial and practical sessions will also be provided to ensure that the module remains practical in nature.

Study time
Type	Hours
Revision	15
Completion of assessment task	55
Tutorial	8
Preparation for scheduled sessions	11
Lecture	30
Wider reading or practice	20
Follow-up work	11
Total study time	150

Assessment

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Coursework	50%
Examination	50%