SDkA: Synthetic Data Integrated k-Anonymity Model for Data Sharing With Improved Utility

SDkA is a new privacy protection method that combines synthetic data (artificially generated data that mimics real data patterns) with k-anonymity (a technique that makes individuals unidentifiable by ensuring each person's data looks like at least k other people's data). The method uses a conditional generative adversarial network (a type of AI that learns to create realistic synthetic data) to improve data quality and quantity while keeping data useful, and adds selective generalization to k-anonymity to avoid over-hiding information.