A privacy-preserving methodology for health data sharing
anonymization, privacy, pseudonymization, LGPD
Society is increasingly computerized, collecting and storing data from its individuals for numerous purposes. People, every day, have their data processed on the internet, data that are related to different areas of their lives. In the healthcare industry, sensitive and confidential data is collected, with intimate details of medical records, where privacy is considered a paramount factor. In this area, data are of paramount importance for its advancement, and its use is necessary beyond the individual's health care. However, due to the social and economic damage that the exposure of this information can bring to the data subjects, and the abuses in the use of personal data that are widely reported, civil society has, increasingly, demanded greater privacy over personal data and greater regulation over the collection and processing of this data. Legislations emerge all over the world to provide the right to privacy for its population. This movement causes a demand for anonymization solutions coming from data providers. Therefore, this work proposes an architecture that makes it possible to anonymize data through anonymization and pseudonymization techniques, aiming at the use of data for secondary purposes, maintaining the privacy of its holders. The expected results are the design of the pseudo(anonymization) architecture and the implementation of a Proof of Concept for exporting data for secondary purposes in the SigSaúde project.