FIT3210 · Securing artificial intelligence systems

Overview

This unit introduces how artificial intelligence (AI) systems are designed, deployed, and secured within modern computing environments, and considers how AI systems can act as targets, attack surfaces, and defensive tools. It covers foundational concepts of AI and machine learning to support understanding of how these systems operate, and examines vulnerabilities that arise across the AI lifecycle, including data, model, and deployment layers. You will explore key security challenges in modern AI systems, including adversarial techniques and how they exploit weaknesses in AI models and applications. You will evaluate emerging defences, and assess risks related to misuse, privacy, and ethics, alongside governance and responsible use. You will apply strategies to improve the security and robustness of AI systems, and develop the ability to communicate security risks and findings to both technical and non-technical audiences.

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook publishes no assessment items for this unit yet.

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

Requisites

Learning outcomes

1. Evaluate risks associated with the use and misuse of AI systems, including privacy, ethical, and societal considerations;
2. Communicate findings about AI system risks and security strategies to technical and non-technical stakeholders using appropriate formats;
3. Investigate vulnerabilities across the model, data, and deployment layers of AI systems through structured analysis and controlled attack/defence activities;
4. Analyse data flows in AI systems and apply information assurance controls to protect them within organisational and governance constraints;
5. Apply appropriate methods to mitigate risks and improve the security and robustness of AI systems through secure design and operational security practices.

Workload

No workload detail published.

Student experience, not official rules. Nothing here changes what the Handbook says.