Re-DPoctor: Real-time health data releasing with w-day differential privacy

TL;DR

Re-DPoctor is a real-time health data release scheme that ensures $w$-day differential privacy, preserving health data patterns and improving utility over existing methods through innovative sampling and budget allocation techniques.

Contribution

It introduces a novel $w$-day differential privacy model tailored for continuous health data from wearables, with new algorithms for pattern protection and adaptive privacy management.

Findings

Achieves better data utility with strong privacy guarantees.

Effectively preserves health data patterns during release.

Outperforms existing methods in real-world experiments.

Abstract

Wearable devices enable users to collect health data and share them with healthcare providers for improved health service. Since health data contain privacy-sensitive information, unprotected data release system may result in privacy leakage problem. Most of the existing work use differential privacy for private data release. However, they have limitations in healthcare scenarios because they do not consider the unique features of health data being collected from wearables, such as continuous real-time collection and pattern preservation. In this paper, we propose Re-DPoctor, a real-time health data releasing scheme with $w$-day differential privacy where the privacy of health data collected from any consecutive $w$ days is preserved. We improve utility by using a specially-designed partition algorithm to protect the health data patterns. Meanwhile, we improve privacy preservation by applying newly proposed adaptive sampling technique and budget allocation method. We prove that Re-DPoctor satisfies $w$-day differential privacy. Experiments on real health data demonstrate that our method achieves better utility with strong privacy guarantee than existing state-of-the-art methods.