2026.06.30

Paper on Privacy Protection Wins the DBSJ Journal Best Paper Award

Toyota Motor Corporation
InfoTech
Shumpei Shiina

The paper "PrivJail: Enforcing Differential Privacy in Python," published in the DBSJ Japanese Journal (Vol. 24-J, Article No. 3), has received the Best Paper Award. The DBSJ Journal Best Paper Award is conferred on the authors of outstanding papers published in a volume of the DBSJ Journal (one of 17 papers selected in 2025). This research was conducted as part of the JST CREST project "Privacy-Preserving Data Analysis and Secure Data Infrastructure for Real Applications," in collaboration with the Taura Laboratory at the University of Tokyo.

PrivJail, developed through this collaborative research, is a Python library that guarantees statistical processing satisfying "differential privacy," a mathematically rigorous standard for privacy protection. PrivJail is publicly available as open-source software:
https://github.com/privjail/privjail

For details, please download the document below (available in Japanese only).