My Genome Belongs to Me: Controlling Third Party Computation on Genomic Data

Journal article
(Original article)


Publication Details

Author(s): Deuber D, Egger C, Fech K, Malavolta G, Schröder D, Thyagarajan SAK, Battke F, Durand C
Journal: Proceedings on Privacy Enhancing Technologies
Publication year: 2019
Volume: 2019
Journal issue: 1
Pages range: 108-132
ISSN: 2299-0984
Language: English


Abstract

An individual's genetic information is possibly the most valuable
personal information. While knowledge of a person's DNA sequence can
facilitate the diagnosis of several heritable diseases and allow
personalized treatment, its exposure comes with significant threats to
the patient's privacy. Currently known solutions for privacy-respecting
computation require the owner of the DNA to either be heavily involved
in the execution of a cryptographic protocol or to completely outsource
the access control to a third party. This motivates the demand for
cryptographic protocols which enable computation over encrypted genomic
data while keeping the owner of the genome in full control. We envision a
scenario where data owners can exercise arbitrary and dynamic access
policies, depending on the intended use of the analysis results and on
the credentials of who is conducting the analysis. At the same time,
they are not required to maintain a local copy of their entire genetic
data and do not need to exhaust their computational resources in an
expensive cryptographic protocol.

In this work, we present METIS, a system that assists the computation
over encrypted data stored in the cloud while leaving the decision on
admissible computations to the data owner. A critical feature of our
system is that the data owner is free from computational overload and
her communication complexity is independent of the size of the input
data and only linear in the size of the circuit's output. METIS is based
on garbled circuits and supports any polynomially-computable function.
We demonstrate the practicality of our approach with an implementation
and an evaluation of several functions over real datasets.


FAU Authors / FAU Editors

Deuber, Dominic
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Egger, Christoph
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Fech, Katharina
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Malavolta, Giulio
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Schröder, Dominique Prof. Dr.
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Thyagarajan, Sri Aravinda Krishnan
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)


External institutions
CeGaT GmbH


How to cite

APA:
Deuber, D., Egger, C., Fech, K., Malavolta, G., Schröder, D., Thyagarajan, S.A.K.,... Durand, C. (2019). My Genome Belongs to Me: Controlling Third Party Computation on Genomic Data. Proceedings on Privacy Enhancing Technologies, 2019(1), 108-132. https://dx.doi.org/10.2478/popets-2019-0007

MLA:
Deuber, Dominic, et al. "My Genome Belongs to Me: Controlling Third Party Computation on Genomic Data." Proceedings on Privacy Enhancing Technologies 2019.1 (2019): 108-132.

BibTeX: 

Last updated on 2018-02-12 at 20:38