UnitLevel 5Postgraduate

FIT5230 AI security

Faculty of Information Technology

FIT5230 AI security is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology, offered in 2027 in Semester 2 at Malaysia. It needs FIT9136.

Credit points
6
Offered in 2027
Semester 2
Malaysia
Assessment
Exam 50%
and 4 other tasks
Workload
144 hours
per semester

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Requisites

After FIT5230

No unit lists FIT5230 as a prerequisite in the 2027 handbook.

Overview

In this unit you will learn first-hand the required skills to eventually become a Chief AI / Data Officer. You will be exposed to the latest technologies deployed by attackers against AI and security, and mechanisms to counter these malicious activities. 

This unit will offer you the opportunity to be engaged in role-playing case studies wherein the coursework assessments will require you to be pitched against each other in a security warfare: security vs anti-security technologies, such as, deepfakes vs anti-deepfakes, adversarial machine learning vs counter adversarial machine learning.

Offerings in 2027

Teaching periodCampusMode
Second semesterMalaysiaOn campus

Assessment

  • Assignment Milestone 1ArtefactThreshold hurdle
    2%
  • Assignment Milestone 2PresentationThreshold hurdle
    8%
  • Assignment Milestone 3PortfolioThreshold hurdle
    25%
  • Assignment Milestone 4WrittenThreshold hurdle
    15%
  • Scheduled final assessment (2 hours and 10 minutes)ExaminationThreshold hurdle
    50%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    identify and analyse malicious technologies deployed by attackers against AI and security such as adversarial machine learning, deepfakes, generative adversarial networks, anti-security;

  2. 2

    devise counter-anti-AI security technologies to combat the anti-AI security techniques deployed by attackers;

  3. 3

    design and formulate AI security or anti-AI security techniques in real-world situations;

  4. 4

    critically assess the level of security offered by existing AI and security systems;

  5. 5

    expose students to the ethical principles and consequences between the dark side and AI for social good.

Workload and teaching

  • Workshops24 hours
  • Laboratories24 hours
  • Teaching approachActive learning
  • Teaching approachRole play
  • Teaching approachPeer assisted learning

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.

Contacts

Chief Examiners
Professor Raphael Phan
Unit Coordinators
Dr Leong Shu Min

Common questions

What are the prerequisites for FIT5230?

You need FIT9136 before you enrol; and FIT5047, FIT5197 or FIT5163 before or alongside it.

When is FIT5230 offered?

In 2027, FIT5230 runs in Semester 2 at Malaysia.

How much work is FIT5230?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does FIT5230 have an exam?

Yes. The exam is worth 50% of the final mark, alongside 4 other tasks.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Information Technology
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
202220232024202520262027