Statistical Disclosure Control

Statistical disclosure control (SDC) aims to protect sensitive information in datasets while preserving data utility for analysis. Current research focuses on developing and evaluating SDC methods for both traditional statistical data releases and increasingly, for machine learning models trained on confidential data, exploring techniques like differential privacy and synthetic data generation. A key challenge is balancing the trade-off between privacy protection and data utility, with ongoing efforts to rigorously assess disclosure risk and improve the accuracy of released information. These advancements are crucial for enabling responsible data sharing and analysis across various sectors, including healthcare, census data, and other sensitive domains.