FIT3183 Malicious AI and dark side security
Faculty of Information Technology
FIT3183 Malicious AI and dark side security is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2020 in Semester 2 at Malaysia. It needs FIT1045 and FIT2093.
- Credit points
- 6
- Offered in 2020
- Semester 2
- Malaysia
- Assessment
- Exam 60%
- and 1 other task
- Workload
- 144 hours
- per semester
This is the 2020 handbook entry. See the 2027 entry.
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Requisites
Before FIT3183
Prerequisites
Pass these before you enrol.
After FIT3183
No unit lists FIT3183 as a prerequisite in the 2020 handbook.
Overview
In this unit you will learn first-hand some of the required skills of a Chief Security 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 gives you the opportunity to engage in role-playing case studies wherein you will be required to participate against other students in a security warfare: security vs anti-security technologies, such as, deepfakes vs anti-deepfakes, forensics vs counter forensics.
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Malaysia | On campus |
Assessment
- In-semester assessmentThreshold hurdle40%
- Examination (2 hours and 10 minutes)ExamThreshold hurdle60%
Learning outcomes
When you finish this unit, you should be able to:
- 1
identify and evaluate malicious technologies deployed by attackers against AI and security such as adversarial machine learning, deepfakes, ransomware, kleptography, cryptovirology, covert exfiltration, anti-forensics, subversion.
- 2
implement counter-anti-security technologies to combat the anti-security techniques deployed by attackers.
- 3
design and deploy security or anti-security techniques in real-world situations.
- 4
critically assess the level of security offered by existing AI and security systems.
- 5
explain the ethical principles between the dark side and cybersecurity for social good.
Workload and teaching
- Lectures24 hours
- Laboratories24 hours
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 activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning and online engagement.
Where it fits
FIT3183 is part of 3 areas of study in the 2020 handbook.
Contacts
- Chief Examiners
- Professor Raphael Phan
Common questions
When is FIT3183 offered?
In 2020, FIT3183 runs in Semester 2 at Malaysia.
How much work is FIT3183?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT3183 have an exam?
Yes. The exam is worth 60% of the final mark, alongside 1 other task.
Which majors and minors include FIT3183?
FIT3183 is part of Advanced computer science, Data science and Software engineering.