Methods To Ensure Privacy Regarding Medical Data -- Including an examination of the differential privacy algorithm RAPPOR and its implementation in "Cryptool 2"

TL;DR

This paper reviews privacy-preserving methods for healthcare data, focusing on anonymization techniques and a detailed examination of the differential privacy algorithm RAPPOR and its implementation in Cryptool 2.

Contribution

It provides a comprehensive overview of privacy methods in healthcare, with an in-depth analysis of RAPPOR's differential privacy application and its practical implementation.

Findings

RAPPOR effectively applies differential privacy to healthcare data.

Anonymization methods vary in suitability for healthcare data.

Implementation in Cryptool 2 demonstrates practical use of RAPPOR.

Abstract

This document examines several applicable methods to ensure privacy of data gathered in the health care sector. To ensure a common understanding of the topic, the introduction explains the need for anonymization methods based on an example. Next, reasons for data collection are introduced in connection to the purpose to protect mentioned data, as well as currently applicable privacy laws to enforce this privacy. The question "What kind of privacy we are talking about and what conditions have to be fulfilled?" is dealt with in the subsequent chapter "Differential Privacy". Thus being established, common anonymization methods are explained and reviewed for their use in the healthcare sector. The RAPPOR algorithm and its differential privacy is dealt with in more detail before coming to a conclusion.