James Cook University Subject Handbook - 2022

CP2421 - Machine Learning for Cybersecurity

Subject Description

Machine learning is one of the most exciting areas being investigated nowadays with applications suitable to countless of different fields. Not surprisingly, many approaches can also be relevant to Cybersecurity, where the ability to correctly identify and classify new and unknown threats may represent the difference between survival and bankruptcy for companies of all sizes. This subject explores different theoretical models for clustering and classification purposes and discusses how they can be applied to solve concrete problems within the cybersecurity domain like, for example, malware detection.

Learning Outcomes

• understand the types of problems that machine learning algorithms can solve
• identify differences in various machine learning algorithms, principles and application purposes of each algorithm
• apply knowledge of machine learning to specific problems relevant to the cybersecurity domain

Subject Assessment

• Written > Examination (centrally administered) - (40%) - Individual
• Written > Case study analysis - (30%) - Individual
• Written > Project report - (30%) - Group

Note that minor variations might occur due to the continuous subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.

Availabilities