The effective de-identification algorithms that balance data usage and privacy are critical. Industries like healthcare, finance, and advertising rely on accurate and secure data analysis. However, existing de-identification methods often compromise either the data usability or privacy protection and limit advanced applications like knowledge engineering and AI modeling.
To address these challenges, we introduce High Fidelity (HiFi) data, a novel approach to meet the dual objectives of data usability and privacy protection. High-fidelity data maintains the original data’s usability while ensuring compliance with stringent privacy regulations.
This article has been indexed from DZone Security Zone