47 citations · 182 across the 18 of their papers we have counts for
3 papers · 1 filter
A multi-language toolkit for the semi-automated checking of research outputs
Richard J. Preen, Maha Albashir, Simon Davy +1
This article presents a free and open source toolkit that supports the semi-automated checking of research outputs (SACRO) for privacy disclosure within secure data environments. S…
Safe machine learning model release from Trusted Research Environments: The SACRO-ML package
Jim Smith, Richard J. Preen, Andrew McCarthy +8
We present SACRO-ML, an integrated suite of open source Python tools to facilitate the statistical disclosure control (SDC) of machine learning (ML) models trained on confidential…
GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)
Emily Jefferson, James Liley, Maeve Malone +16
TREs are widely, and increasingly used to support statistical analysis of sensitive data across a range of sectors (e.g., health, police, tax and education) as they enable secure a…