Privacy Preserving Machine Learning

Emerging Technologies – led by Monash Faculty of IT

Machine learning (ML) services improve businesses and provide ready-made intelligence for end-user applications. But there’s a growing discordance between the rapid growth of ML and renewed awareness of privacy protection.

The problem

Data from individuals can carry private information, and ML models are deemed intellectual properties. With a surge in new technologies, we must protect both people and businesses by guaranteeing the security of sensitive information carried in databases and models.

This program strongly aligns with the ‘Digital SMEs’ and ‘Dynamic and emerging tech sector’ priority areas in the Australian Government's Digital Economy Strategy 2030. It also focuses on the Modern Manufacturing Initiative and National Manufacturing Priorities ‘Medical Products’ and ‘Recycling & Clean Energy’.

The goal

In addition to cultivating the next generation of Australia’s workforce that’s skilled in privacy-preserving machine learning (PPML), this project aims to pave the way for broad market adoptions of PPML – making it an integral part of the country’s future digital economy and society.

We will explore emerging privacy-enhancing techniques for realising PPML systems, address practical challenges during deployment and drive its adoption across Australia.

Outcomes you’ll drive

Build a national workforce skilled in ML and cybersecurity.
Deliver new PPML technologies and systems.
Generate cohort-based, industry-oriented research collaborations and graduate training programs within the primary focuses of our partners and associated sectors.
Uplift the IT, medical AI and e-commerce industries, and our partners, through upgraded product lines, new marketable PPML products and innovative solutions for safeguarding customers and intellectual property.
Safeguard sensitive data from end-users and increase their confidence in using our partner’s products.
Ease privacy and security concerns around adopting ML-based solutions – encouraging more users and facilitating the digital economy transformation in Australia.

Your study experience

As part of this research cohort, you will gain multi-disciplinary knowledge and skills in AI, ML and cybersecurity. You will work with leading supervisors from academia and industry to:

Explore emerging privacy-enhancing techniques and design new algorithms and protocols for realising PPML system
Investigate real-world PPML deployment and settings including ML as a service, federated learning and on-device ML
Integrate and apply PPML systems to priority sectors such as digital SMEs, medical products and e-commerce.

What you will receive

- $40,500 annual stipend for 3.5 years
- Industry placement for 6 months (or equivalent total duration)
- $5,000 annual research expenses (minimum)
- $5,000 international travel (minimum)
- Expert academic and industry supervision
- CSIRO-led 9-week industry training
- $40,500 annual stipend for 2 years
- Industry placement for 3 months (or equivalent total duration)
- $5,000 annual research expenses (minimum)
- $5,000 international travel (minimum)
- Expert academic and industry supervision
- CSIRO-led 9-week industry training
$10,000 stipend
Industry placement for 6 days (minimum)
$5,000 research expenses (minimum)
Expert academic and industry supervision