Confidential data

We’ve developed technology that allows personal or commercially sensitive data to be statistically analysed while protecting confidentiality and privacy.

The Challenge

Balancing data use with privacy

Many organisations have large databases of confidential or private information. They want to allow analysis of their data to help them make better decisions, the outcomes of which may, in turn, benefit individuals.

These organisations, or data custodians, may include:

  • health services such as hospitals, Medicare and state government health departments
  • social welfare agencies such as Centrelink and the Department of Families, Housing, Community Services and Indigenous Affairs
  • financial institutions such as banks or tax departments
  • national statistical services such as the Australian Bureau of Statistics.

Privacy is a complex issue. People and organisations rightly expect that no-one will have access to their private information unless authorised. Some types of data are considered more sensitive than others. Privacy concerns, real or imagined, prevent some valuable analyses being done at all.

We have identified a clear need for a range of different solutions that allow a balance between the need to maintain privacy and providing information for evidence-based decision-making.

Our Response

Introducing Privacy-Preserving Analytics

We assessed solutions and approaches being applied around the world including the removal of data, such as name and gender, from records and adding ‘noise’ to the data or swapping data between records.

However the downside of these approaches is that they may:

  • compromise data quality by distorting the dataset
  • limit data usefulness by removing or changing important information
  • introduce difficulties in the analysis stage
  • fail to sufficiently confidentialise the data.

Our solution is Privacy-Preserving Analytics, or PPA. Our demonstrator software performs statistical analyses in a secure environment, and then filters the results delivered to the user so that confidentiality and privacy are protected.

PPA performs analysis on 'raw' unit record level data without the need for the data custodian to release the data. The data always remain under the direct control of the data custodian. Even the data analyst has no direct access to the data but works with a purpose-built ‘remote control’ panel.

PPA is designed to:

  • analyse raw data remotely, in a secure environment
  • prevent a user reconstructing any individual record
  • be part of a bigger privacy solution which incorporates governance and security.

The Results

Opening up access to data

Future application of PPA could open up access to data which is currently not available for research and policy analysis.

For example, the Population Health Research Network has been established to provide improved accessibility to Australian health related data for the research sector, and PPA could provide an access pathway.

More widely, services improvement and innovation often requires access to personal and/or confidential services delivery data, and PPA could provide a means of balancing the use of the data with privacy and confidentiality protection.

Enquiries

Have an enquiry about this page?

Contact us

Do business with us to help your organisation thrive

We partner with small and large companies, government and industry in Australia and around the world.

Contact us now to start doing business