Making PosgreSQL Differentially Private for Transparent AI – DIFPRIPOS
The general objective is to propose a "privacy preserving" tool 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 production 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, existing or to be built, for SPJA and DUMP queries, to integrate them into PostgreSQL Anonymizer and hence to prohibit individual inferences from such queries.
Project coordination
Jean-François COUCHOT (INSTITUT FRANCHE-COMTE ELECTRONIQUE MECANIQUE THERMIQUE ET OPTIQUE - SCIENCES ET TECHNOLOGIES)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
LIFO EA 4022 LABORATOIRE D'INFORMATIQUE FONDAMENTALE D'ORLÉANS
LIRIS UMR 5205 - LABORATOIRE D'INFORMATIQUE EN IMAGE ET SYSTEMES D'INFORMATION
FEMTO-ST INSTITUT FRANCHE-COMTE ELECTRONIQUE MECANIQUE THERMIQUE ET OPTIQUE - SCIENCES ET TECHNOLOGIES
DALIBO
Centre Inria de Saclay
Help of the ANR 338,077 euros
Beginning and duration of the scientific project:
September 2023
- 48 Months
