A Systematic Literature Review on Wearable Health Data Publishing under Differential Privacy
Munshi Saifuzzaman, Tajkia Nuri Ananna, Mohammad Jabed Morshed, Chowdhury, Md Sadek Ferdous, Farida Chowdhury

TL;DR
This paper systematically reviews how differential privacy techniques are applied to protect individuals' wearable health data, highlighting current methods, limitations, and future research directions.
Contribution
It provides a comprehensive analysis of existing differential privacy approaches in wearable health data publishing, identifying gaps and proposing future research directions.
Findings
Differential privacy is increasingly used for wearable health data.
Current solutions have limitations in utility and privacy balance.
Future research should address scalability and real-world deployment challenges.
Abstract
Wearable devices generate different types of physiological data about the individuals. These data can provide valuable insights for medical researchers and clinicians that cannot be availed through traditional measures. Researchers have historically relied on survey responses or observed behavior. Interestingly, physiological data can provide a richer amount of user cognition than that obtained from any other sources, including the user himself. Therefore, the inexpensive consumer-grade wearable devices have become a point of interest for the health researchers. In addition, they are also used in continuous remote health monitoring and sometimes by the insurance companies. However, the biggest concern for such kind of use cases is the privacy of the individuals. There are a few privacy mechanisms, such as abstraction and k-anonymity, are widely used in information systems. Recently,…
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Taxonomy
TopicsPrivacy-Preserving Technologies in Data · Privacy, Security, and Data Protection
