ITI5124 · Emerging topics for cybersecurity in practice

Overview

This unit aims to provide you with advanced knowledge of cybersecurity. Advancements in cloud services, mobile computing, and machine learning bring much convenience to our lives, improve our productivity in daily work, and provide us with personalised services. Despite many benefits, these new paradigms incur aggravated security and privacy concerns. End-users, enterprises, and governments face growing threats from sophisticated cyber attacks. This unit will study advanced cybersecurity technologies to address those threats in the current practice. Topics include design and implementation of advanced cryptosystems for high-performance applications such as encrypted databases, cryptographic protocols and hardware-assisted approaches for secure computing applications such as privacy-preserving machine learning, and practical post-quantum cryptography that can address the emerging threats of quantum computers. Learning activities will focus on understanding security and privacy issues in cloud and networked systems, encrypted search techniques, cloud storage security, secure multi-party computation techniques, trusted computing, and lattice-based cryptography.

Offerings

The Handbook publishes no offerings for this unit.

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

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

Requisites

Learning outcomes

1. Identify security and privacy issues in cloud, networked, and machine learning systems;
2. Describe the operations of several advanced cryptosystems and protocols and their underlying assumptions and applications;
3. Apply hardware-assisted techniques to design secure and trustworthy systems;
4. Explain advanced attacks against cryptosystems and machine learning systems;
5. Analyse the strengths and limitations of emerging cybersecurity technologies

Workload

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.

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