Privacy, Risk, Anonymization and Data Sharing in the Internet of Health Things

Abstract

This paper explores a specific risk-mitigation strategy to reduce privacy concerns in the Internet of Health Things (IoHT): data anonymization. It contributes to the current academic debate surrounding the role of anonymization in the IoHT by evaluating how data controllers can balance privacy risks against the quality of output data and select the appropriate privacy model that achieves the aims underlying the concept of Privacy by Design. It sets forth several approaches for identifying the risk of re-identification in the IoHT as well as explores the potential for synthetic data generation to be used as an alternative method to anonymization for data sharing.