Welcome !


  • FEMTO-ST/ Université de Franche-Comté (UFC) : J.-François COUCHOT  and  Veronika REHN-SONIGO
  • LIRIS/INSA-Lyon :  Nadia BENNANI
  • The DALIBO cooperative society : Damien CLOCHARD
  • LIFO / INSA-CVL : Cédric EICHLER, Adrien BOIRET, and Benjamin, NGUYEN
  • INRIA/Comète : Catuscia PALAMIDESSI, and Heber HWANG-ARCOLEZI


  • The general objective is to propose to implement and to evaluate a  "privacy preserving" approach for interpreting SQL queries in the sense of differential confidentiality that can be integrated into PostgreSQL. These queries will range from the Select-Project-Join-Aggregation (SPJA) form to the export of releases (DUMP) of a part of the database in order to be able to work on it as if it contained no sensitive data. This project is based on the PostgreSQL Anonymizer tool developed by DALIBO, a member of the consortium. Specifically, the main objective is to extend the anonymization models already integrated in this tool (pseudonymization, k-anonymization and addition of noise) to other models verifying DP, some relaxations and to be built, for SPJA and DUMP queries. All of them will be integrated into PostgreSQL Anonymizer and validated thanks to open platform.
  • It will result in a tool to minimise inferences from responses to queries on this DBMS when interpreted by the PostgreSQL Anonymizer extension.


  •  Agence Nationale de la Recherche, AAPG 2023 PRCE