Home » Project of the week » PROJECT OF THE WEEK - SODA
19/08/2019 to 23/08/2019

MORE and more data is being generated. Analyzing this data drives knowledge and value creation across society. But to unlock this potential requires sharing of often personal data between organizations, but this meets unwillingness from data subjects and data controllers alike. So there is a need of techniques that protect personal information for data access, processing, and analysis.

The SODA project aims to tackle exactly data protection and anonymization issue identified by the BDVA, enabling practical privacy-preserving analytics on Big Data by significant improvement of MPC techniques for privacy-preserving Big Data processing.

SODA will provide analytics on sensitive information beyond the privacy-utility trade-off and will therefore enable to unlock the immense potential hidden in privacy sensitive Big Data.

To address the issues, here are the four (4) main approaches of the SODA project:

  1. ​To enable Multi Party Computation (MPC) techniques for big data applications by scaling the performance. We follow a use case-driven approach, combining expertise from the domains of MPC and data analytics.
  2. To combine these improvements with a multidisciplinary approach towards privacy. By enabling differential privacy in the MPC setting aggregated results will not leak individual personal data. Legal analysis performed in a feedback loop with technical development will ensure improved compliance with EU data privacy regulation.
  3. The  USER STUDIES performed in a feedback loop with our consent control component will make data subjects more confident to have their data processed with our techniques.
  4. Finally, to validate our approach, by applying our results in a medical demonstrator originating from Philips practice and in a use case arising from the ICT-14.b data experimentation incubators. The techniques will be subjected to public hacking challenges. The technical innovations will be released as open-source improvements to the FRESCO MPC framework.

This means data does not need to be shared, only made available for encrypted processing.

The SODA consortium is constituted of 5 members, headed by PHILIPS ELECTRONICS Netherland B.V. The Data Science department in Philips Research, headed by Prof. Milan Petković, combines experienced researchers in the domains of data management, analytics, security and advanced computing.

The project supports cohesive and secure use of personal (health) data, demonstrated on the SODA Model.

Step 1: Health data - There is a huge potential in using the massive amounts of data that healthcare entities and patients have collected over the past decades. At the same time, personal health information needs to be protected.

Step 2: Security techniques - The research team uses two basic security techniques to anonymise data: Secure multiparty computation and differential privacy.

Step 3: Big data research and analytics - Enables companies, authorities and researchers to perform data analytics on private (big) data without compromising on security.

Stay tuned as we bring you more details about this SODA project and how they will help the cybersecurity and privacy community in protecting personal information for data access, processing, and analysis. 

Check out the latest news about the SODA project in Cyberwatching Project Hub.

You can visit their official website:

Monday, 19 August, 2019


The pdf presentations of the European Cluster for Securing #Critical

Future Events

The third Annual Fraud & Financial Crime Europe will focus on analysing the risks to determine the solutions in combating Fraud and Financial Crime.

01/09/2020 to 02/09/2020

Information security and privacy have already been established as some of the most crucial aspects of technology especially in a world that is migrating to digital applications by the day. This has inevitably led to the emergence of technologies that support the safety and dependability of the ever-increasing sensitive data handled by these applications. Additionally, besides these technologies which target security by their design, there are other technologies, such as machine learning, which could potentially be applied to security in innovative schemes. 

17/09/2020 to 18/09/2020