Data61’s expertise in data science necessitates a close understanding of issues around privacy - the protection of information about individuals or groups to which access must be restricted or carefully controlled. Our work in this area goes beyond simple awareness of issues - we are conducting research and creating products that works to improve the protection of sensitive information for Australian citizens, protect valuable IP for businesses, and enable vital research and analysis for governments. 


Key areas

Encrypting data

N1 Analytics is a technology developed by Data61 that sends the compute to where the data resides and any data required by other providers is encrypted using homomorphic encryption. Companies can safely unlock and use confidential data by using N1 Analytics, while ensuring confidentiality and privacy for all parties.

Privacy Preserving Linkage enables matching and linking records across datasets without revealing or releasing the identifying data. It works even if there are errors in the data.

Confidential Statistics enables statistical queries across multiple data sets to compute counts, sums and averages of selections.

Privacy preserving transformation of data

Data61’s privacy experts have demonstrated the use of a privacy preserving algorithms on a number of sensitive datasets. Individual data is mathematically obscured, but the ‘shape’ remains the same. Our team uses mathematical proofs to ensure that the privacy of individuals is protected through a transformation process that cannot be reversed - enabling analysis of broad trends whilst protecting the privacy of individuals.

Front cover of The Deidentification Decision-Making Framework

The De-Identification Decision-Making Framework


We’ve developed a practical guide to de-identification for government agencies and businesses including not-for-profit and private sector organisations. Our framework can help data custodians to identify and address the key factors relevant to their particular data sharing or release situation, including privacy risk analysis and control, stakeholder engagement, and impact management.

In addition to this work, we have begun work on assessing the risk of re-identification in both original and de-identified datasets. This is the 'Reidentification Ready Reckoner' project. 

Research, expertise and other products

We engaged in research to develop guidelines to allow publication of the results of analysis on personally private or commercially sensitive data, while protecting privacy and confidentiality.

  • SenDA - Data61 is developing software and a user interface for data researchers to access large sets of de-identified government data at the unit record level, and to access longitudinal survey data.
  • Gait authentication - we developed new technology which uses the way a person walks, their gait, to power wearable devices. The technology also has the potential to be used as a new authentication method, which could replace passwords, pins or fingerprints.
  • Anonalytix - iour software suite that enables de-identification of personally identifiable information (PII data) and delivers a quantifiable privacy guarantee, while preserving the utility of data analytics.
  • VPN privacy- we released a study that examined privacy issues around VPN apps, finding that many were lacking. 
  • Privmetrics - We are developing PrivMetrics framework that enables users to make informed decisions about the use of these third party apps by providing them with an analysis on their privacy leakages and wherever possible recommending alternative apps with the same functionality as the apps they are considering which better protect their overall privacy.
  • PRADA - stands for Privacy Risk Assessment and Defense Apparatus. It is a research and development project at the Networks Group of Data61. Its main goal is to build a production quality privacy management dashboard to oversee data disclosure. The user will be able to analyse and modify their datasets using some built-in privacy risk assessment tools and privacy-preserving algorithms. 
  • Find even more Privacy and Network Security projects

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