A formal quantitative study of privacy in the publication of official educational censuses in Brazil
Gabriel H. Nunes, Mário S. Alvim, Annabelle K. McIver · 2022
We present a summary of the work done in the dissertation "A formal quantitative study of privacy in the publication of official educational censuses in Brazil", including its contributions and impacts so far. The dissertation presents a systematic refactoring of the conventional treatment of privacy analyses, based on mathematical concepts from the framework of Quantitative Information Flow (QIF). This brings three principal advantages: flexibility, allowing for precise quantification and comparison of privacy risks for attacks both known and novel; computational tractability for very large, longitudinal datasets; and explainable results both to politicians and to the general public. We apply our approach to a very large case study: the educational censuses in Brazil, which comprise over 90 attributes of approximately 50 million individuals released longitudinally every year since 2007.