We are a collaborative research group working on the development and application of Quantitative Information Flow (QIF), a mathematical framework for reasoning about information leaks in secure systems.
Our name “topete” is the Portuguese word for “quiff”.
We maintain a curated list of QIF projects, tools, and resources.
Check Awesome QIF Also check the book!
The project A robust and explainable framework based on QIF for assessing big data privacy risks was awarded in the 2021 Google Latin America Research Awards!
The paper Flexible and scalable privacy assessment for very large datasets with an application to official governmental microdata has been accepted at PETS (Privacy Enhancing Technologies Symposium) 2022
The paper A novel reconstruction attack on foreign-trade official statistics, with a Brazilian case study has been accepted at PETS 2022
The paper Universal Optimality and Robust Utility Bounds for Metric Differential Privacy has been accepted at CSF (Symposium on Computer Security Foundations) 2022