Software Innovation Institute · ANU
Anushka Vidanage
I'm Research Fellow|
I research how to protect people's privacy while still enabling their data to be used effectively. My work focuses on distributed secure data management, differential privacy, and federated learning, with a particular interest in privacy-preserving record linkage. For the past five years, I had the opportunity to lead multidisciplinary data science projects, mentor researchers, engineers, and students, and work with a wide range of stakeholders to deliver impactful project outcomes. I'm passionate about applying privacy, data security, and machine learning to solve real-world problems.
Research focus
Privacy-preserving record linkage (PPRL)
Cryptanalysis attacks on PPRL techniques, and the design of more robust methods that can withstand them.
Data privacy and security
Differential privacy, cryptography, and federated learning across real-world applications.
Decentralised data management
Solid Personal Online Datastores model, where people hold their own data and grant access to it rather than surrendering it.
Latest news
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Solid 2026 Hackathon Wrap-Up: Three Days Building the Decentralised Web in Canberra
The Solid 2026 Hackathon has wrapped up. See the wrap-up report
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Solid 2026 Hackathon: Building the Decentralised Web in Canberra
Organising the first ever Solid Hackathon in Canberra. See the announcement
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The use of differential privacy for privacy-preserving record linkage: Protecting the bits but not the people
PhD student research published in the Information Systems journal.
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Implementing Encrypted Private Data Sharing between Personal Data Vaults
Our paper on secure data management framework for Solid PODs published in the 4th Solid Symposium.
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Information leakage in the practical linking of sensitive data: Parties, protocols, and adversaries
Our paper on evaluating how information leakage occurs in practical record linkage scenarios published in the Information Systems journal