Abstract
Big data are analyzed to reveal patterns, trends and associations, especially relating to human behavior and interactions. However, according to the European General Data Protection Regulation (GDPR), which is becoming a de facto global data protection standard, any intended uses of personally identifiable information (PII) must be clearly specified and explicitly accepted by the data subjects. Furthermore, PII cannot be accumulated for secondary use. Thus, can exploratory data uses on PII be GDPR-compliant? Hardly so.
Resorting to anonymized data sets instead of PII is a natural way around, for anonymized data fall outside the scope of GDPR. The problem is that anonymization techniques, based on statistical disclosure control and privacy models, use algorithms and assumptions from the time of small data that must be thoroughly revised, updated or even replaced to deal with big data.
Upgrading big data anonymization to address the previous challenge needs to empower users (by giving them useful anonymized data), subjects (by giving them control on anonymization) and controllers (by simplifying anonymization and making it more flexible).
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Acknowledgment and Disclaimer
Partial support to this work has been received from the European Commission (project H2020-700540 “CANVAS”), the Government of Catalonia (ICREA Acadèmia Prize to J. Domingo-Ferrer and grant 2017 SGR 705), and from the Spanish Government (project RTI2018-095094-B-C21). The author is with the UNESCO Chair in Data Privacy, but the views in this paper are his own and are not necessarily shared by UNESCO.
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Domingo-Ferrer, J. (2019). Personal Big Data, GDPR and Anonymization. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà, D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_2
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DOI: https://doi.org/10.1007/978-3-030-27629-4_2
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