Evaluation of Re-identification Risk using Anonymization and Differential Privacy in Healthcare
Ritu Ratra, Preeti Gulia, Nasib Singh Gill · International Journal of Advanced Computer Science and Applications · 2022
In the present scenario, due to regulations of data privacy, sharing of data with other organization for research or any medical purpose becomes a big hindrance for different healthcare organizations. To preserve the privacy of patients seems like a crucial challenge for Healthcare Centre. Numerous techniques are used to preserve the privacy such as perturbation, anonymization, cryptography, etc. Anonymization is well known practical solution of this problem. A number of anonymization methods have been proposed by researchers. In this paper, an improved approach is proposed which is based on k-anonymity and differential privacy approaches. The purpose of proposed approach is to prevent the dataset from re-identification risk more effectively from linking attacks using generalization and suppression techniques.