Scalable and Usable Privacy Preserving Techniques

In a data driven society, sharing data among organizations is
crucial for the growth of research and businesses. Often data sets
contain sensitive personal information which must be protected
under the GDPR regulations. In this research, we tackled the
problem of scalable and usable statistical disclosure technologies.
The primary focus of this research was to propose solutions upon
which data driven organization can exploit sophisticated SDC
techniques. This research resulted in various directions as below:
- Scientific Articles: Three research papers and one work in
progress paper. All accepted in different conferences.
- Education: Two students graduate projects and several
practical workshops in different minors in CMI – INF.
- Presentations: different presentations in Creating 010, and
organizations like UWV and Erasmus MC.
- Interview: Hoogtepunten 2020, Creating 010.
- Software Tool: A web-based software tool (proof of
concept) that can be used to outsource data anonymization
projects.

A huge amount of data are being generated, collected, analysed and distributed in a fast pace in our daily life. This data growth requires efficient techniques for analysing and processing high volumes of data, for which preserving privacy effectively is a crucial challenge and even a key necessity, considering the recently coming into effect privacy laws (e.g., the EU General Data Protection Regulation-GDPR). Companies and organisations in their real-world applications need scalable and usable privacy preserving techniques to support them in protecting personal data.

This research focuses on efficient and usable privacy preserving techniques in data processing. The research will be conducted in different directions:
- Exploring state of the art techniques.
- Designing and applying experiments on existing tool-sets.
- Evaluating the results of the experiments based on the real-life case studies.
- Improving the techniques and/or the tool to meet the requirements of the companies.

The proposal will provide results for:
- Education: like offering courses, lectures, students projects, solutions for privacy preservation challenges within the educational institutes.
- Companies: like providing tool evaluation insights based on case studies and giving proposals for enhancing current challenges.
- Research centre (i.e., Creating 010): like expanding its expertise on privacy protection technologies and publishing technical reports and papers. This research will be sustained by pursuing following up projects actively.