The APDCAT promotes the use of synthetic data to protect privacy in the field of research, research and technological development

The Catalan Data Protection Authority (APDCAT), in collaboration with the School of Public Administration of Catalonia (EAPC), has organized the day 'Synthetic data and privacy', as part of the specialized training course data protection representatives who promote both entities. The objective has been to debate and analyze the potential of using this type of artificial data generated from original data, as a privacy protection measure. Specifically, as an example of privacy by design and by default.

The director of the APDCAT, Meritxell Borràs, opened the session, in which the professor of the Rovira i Virgili University, director of CYBERCAT and of the UNESCO Chair in Data Privacy, Josep Domingo-Ferrer, participated. During his speech, Borràs argued that any methodology or tool that minimizes or avoids the processing of personal data and allows objectives to be achieved in an environment of innovation and continuous development must be promoted. Thus, he recalled that these data do not refer to any real person, and highlighted that, in an increasingly data-driven society like ours, the right to data protection has become the way to protect the set of rights and freedoms.

For his part, Josep Domingo-Ferrer has defended that synthetic data is an attractive option in data protection, because they can be used to publish data without violating privacy requirements, to facilitate the development of software with realistic simulated data or to educational purposes.

The conference served to review the uses of synthetic data, the main methods of generating this type of data, the measures of usefulness and confidentiality to evaluate them and ensure that they are not real personal data and the permutation method as a case study.

The use of synthetic data is gaining strength in various areas of today's society. For example, they help test algorithms that need an immense amount of labeled data to train and where limits on the use of the data are difficult to establish. Therefore, they are configured as a good tool to protect privacy in the field of innovation and research with the use of massive data.