How you can harness data in a privacy-friendly way
Envision it: better treatment methods for patients by learning from the successes and failures of doctors and pharmaceutical companies. Detecting money laundering activities by bringing together data from different banks. Combining data from large groups of people or organisations can lead to new insights, but how do you do this without violating the privacy of citizens? And how do you use sensitive business information to gain new insights? You can read all about this in the ‘Finally, a privacy-friendly way to harness data’ whitepaper.
After reading the whitepaper, you have gained knowledge about:
Economic potential. Recent analyses show that the availability and exchange of data can lead to economic growth of 1.5% of GDP (source OECD, „Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across Societies,” OECD Publishing, Paris, 2019). How can your organisation profit from this?
Societal impact. Personalised healthcare is an example of this. In addition, government bodies can improve their services for citizens.
Applications. We show cases that include TNO working together with partners. Read how smart data analyses can reduce the impact of cancer and how data analyses can help fight poverty.
Technology. How do insights without data sharing actually work? How is the privacy of citizens safeguarded? And how can you harness data without sharing competitive information? We explain how Multi-Party Computation and Federated Learning work.
Combining data for better government services
Provide better services for citizens without violating their privacy.
In our opinion, it is time for a new starting point in the processing of sensitive data: moving away from the traditional centralised method of data processing and towards distributed data processing. You don’t need to actually have the data to create value from it – so don’t share data but use insights from diffuse data sources while ensuring privacy and confidentiality.
MPC as fraud detection and anti-money laundering tool
Find out how MPC can help combat fraud and money laundering without violating privacy.
Secure multi-party computation: jointly analysing sensitive data without sharing it
The analysis of data from different sources is becoming increasingly important. At the same time, relevant data is often too sensitive to be casually shared with others. How can organizations share information...
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