ARC Future Fellowships - Grant ID: FT220100391

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/FT220100391

Funding Status
Active

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Funded Activity Summary

Learning Software Security Analysers with Imperfect Data. This project aims to systematically investigate next-generation learning-based software security analysis to detect vulnerabilities in real-world large-scale software. The expected learning-based foundation will support the handling of imperfect data in order to provide a precise, scalable and adaptive security analysis of the critical software components, thus capturing important security vulnerabilities missed by existing approaches. The success of this project will further enhance the international competitiveness of Australian research in this important field and will benefit any Australian industry and business where software systems are deeply-rooted, such as transportation, smart homes, medical devices, defence and finance.

Funded Activity Details

Start Date: 30-06-2023

End Date: 29-06-2027

Funding Scheme: ARC Future Fellowships

Funding Amount: $892,310.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Deep learning | Software and application security | Software engineering | Software testing verification and validation

ANZSRC Socio-Economic Objective (SEO)

Other Keywords

Application Software Packages | Deep learning | Software and application security | Software engineering | Software testing verification and validation

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