We have performed an analysis (please see Appendix B) of the syllabus of the AI units and cybersecurity units offered by the Faculty of IT (FIT), and identified that there are gaps in the following areas for AI:

• Computer vision: which is a major sub-field of AI, is relevant tosecurity and appeals to the public because it involves visually sensingand processing the real world
• AI techniques to solve security problems: current FIT units treat AIand cybersecurity separately although in the real world and in scientificliterature they are permeating across each other; as well as there are gaps in the following areas for cybersecurity:
• Security+AI: indeed, security attacks and defenses are increasingly involving AI, andvice versa AI techniques in recent years are designed for robustnessagainst malice (e.g. adversarial machine learning, generativeadversarial networks - GANs, deepfakes)
• Security in terms of surveillance
• Privacy: which is an equally important issue in our current society ofmass surveillance and diverse sensing due to IoT

To champion Monash and FIT?s aim of IT for social good, we need to consider more types of security beyond the current treatment of crypto, network security, forensics and software security; as many other security issues are adversely impacting the society e.g.

• Deepfakes and the threat of AI
• Security and privacy issues of social media
• Security and privacy issues of mass surveillance and IoT sensing

To our best knowledge, no such unit exists in other universities that unify the adversarial & dark side aspects of AI and cybersecurity. The closest ones may be those on cryptovirology which focus on cryptology or AI courses which have some treatment of the robustness of AI to attacks.

For introduction in Semester 2, 2020.

12/04/2021 - Admin: updating assessment to add breakdown of in-semester assessment as per CE's email.

On successful completion of 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

029901

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.

On-campus

Examination: (2 hours and 10 minutes) 60% In-semester assessment: 40%

In-semester assessment breakdown:

1. Assignment Milestone 1: 2%
2. Assignment Milestone 2: 8%
3. Assignment Milestone 3: 20%
4. Assignment Milestone 4: 10%

This unit contains hurdle requirements which you must achieve to be able to pass the unit. The consequence of not achieving a hurdle requirement is a fail grade (NH) and a maximum mark of 45 for the unit.

Minimum total expected workload equals 12 hours per week comprising:

Contact hours:

• Two hour lecture
• One 2-hour laboratory

Additional requirements:

• A minimum of 8 hours independent study per week for completing lab and project work, private study and revision

FIT

FIT1045, FIT2093