Discovery Projects - Grant ID: DP220102784

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP220102784

Funding Status
Active

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Funded Activity Summary

MemberGuard: Protecting Machine Learning Privacy from Membership Inference. Machine Learning has become a core part of many real-world applications. However, machine learning models are vulnerable to membership inference attacks. In these attacks, an adversary can infer if a given data record has been part of the model's training data. In this project, the team aims to develop new techniques that can be used to counter these attacks, such as 1) new analytical models for membership leakage, 2) new methods for susceptibility diagnosis, 3) new defences that leverage privacy and utility. Data-oriented services are estimated to be valuable assets in the future. These techniques can help Australia gain cutting edge advantage in machine learning security and privacy and protect its intellectual property on these services.

Funded Activity Details

Start Date: 01-01-2022

End Date: 31-12-2024

Funding Scheme: Discovery Projects

Funding Amount: $450,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Computer Software | Computer System Security |

ANZSRC Socio-Economic Objective (SEO)

Computer Software and Services not elsewhere classified | Application Tools and System Utilities

Other Keywords

Application Tools and System Utilities | Computer Software | Computer Software and Services not elsewhere classified | Computer System Security

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