Private Reverse Top-k Algorithms Applied on Public Data of COVID-19 in the State of Ceará

Abstract

In this article we propose a differentially private reverse top-k query. Our strategy allows obtaining the less frequent data according to a search criteria, with a high guarantee of privacy of the individuals who contributed with personal data in the original database. We apply our strategy on public data for COVID-19 in the State of Ceará using two different queries. Our experimental results show that the result of the proposed top-k query returns a high degree of similarity to the result of a conventional top-k query, when the chosen budget is suitable, providing useful results for researchers, while ensuring a low probability of re-identification of individuals arising from the properties of differential privacy.