Evaluation of Re-identification Risk using Anonymization and Differential Privacy in Healthcare

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