[Resource Topic] 2016/411: Polymorphic Encryption and Pseudonymisation for Personalised Healthcare

Welcome to the resource topic for 2016/411

Title:
Polymorphic Encryption and Pseudonymisation for Personalised Healthcare

Authors: Eric Verheul, Bart Jacobs, Carlo Meijer, Mireille Hildebrandt, Joeri de Ruiter

Abstract:

Polymorphic encryption and Pseudonymisation, abbreviated as PEP, form a novel approach for the management of sensitive personal data, especially in health care. Traditional encryption is rather rigid: once encrypted, only one key can be used to decrypt the data. This rigidity is becoming an every greater problem in the context of big data analytics, where different parties who wish to investigate part of an encrypted data set all need the one key for decryption. Polymorphic encryption is a new cryptographic technique that solves these problems. Together with the associated technique of polymorphic pseudonymisation new security and privacy guarantees can be given which are essential in areas such as (personalised) healthcare, medical data collection via self-measurement apps, and more generally in privacy-friendly identity management and data analytics. The key ideas of polymorphic encryption are: 1. Directly after generation, data can be encrypted in a polymorphic' manner and stored at a (cloud) storage facility in such a way that the storage provider cannot get access. Crucially, there is no need to a priori fix who gets to see the data, so that the data can immediately be protected. For instance a PEP-enabled self-measurement device will store all its measurement data in polymorphically encrypted form in a back-end data base. 2. Later on it can be decided who can decrypt the data. This decision will be made on the basis of a policy, in which the data subject should play a key role. The user of the PEP-enabled device can, for instance, decide that doctors $X,Y,Z$ may at some stage decrypt to use the data in their diagnosis, or medical researcher groups $A, B, C$ may use it for their investigations, or third parties $U,V,W$ may use it for additional services, etc. 3. This tweaking’ of the encrypted data to make it decryptable by a specific party can be done in a blind manner. It will have to be done by a trusted party who knows how to tweak the ciphertext for whom. This PEP technology can provide the necessary security and privacy infrastructure for big data analytics. People can entrust their data in polymorphically encrypted form, and each time decide later to make (parts of) it available (decryptable) for specific parties, for specific analysis purposes. In this way users remain in control, and can monitor which of their data is used where by whom for which purposes. The polymorphic encryption infrastructure can be supplemented with a pseudonymisation infrastructure which is also polymorphic, and guarantees that each individual will automatically have different pseudonyms at different parties and can only be de-pseudonymised by participants (like medical doctors) who know the original identity. This white paper provides an introduction to Polymorphic Encryption and Pseudonymisation (PEP), at different levels of abstraction, focusing on health care as application area. It contains a general description of PEP, explaining the basic functionality for laymen, supplemented by a clarification of the legal framework provided by the upcoming General Data Protection Regulation (GDPR) of the European Union. The paper also contains a more advanced, mathematically oriented description of PEP, including the underlying cryptographic primitives, key and pseudonym managment, interaction protocols, etc. This second part is aimed at readers with a background in computer security and cryptography. The cryptographic basis for PEP is ElGamal public key encryption, which is well-known since the mid 1980s. It is the way in which this encryption is used — with re-randomisation, re-keying and re-shuffling — that is new. The PEP framework is currently elaborated into an open design and open source (prototype) implementation at Radboud University in Nijmegen, The Netherlands. The technology will be used and tested in a real-life medical research project at the Radboud University Medical Center.

ePrint: https://eprint.iacr.org/2016/411

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