Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

Alexandros Bampoulidis, Alessandro Bruni, Lukas Helminger, Daniel Kales, Christian Rechberger, Roman Walch*

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: KonferenzbeitragPaperBegutachtung

Abstract

Recent work has shown that cell phone mobility data has the
unique potential to create accurate models for human mobility and con-
sequently the spread of infected diseases [74]. While prior studies have
exclusively relied on a mobile network operator’s subscribers’ aggregated
data in modelling disease dynamics, it may be preferable to contemplate
aggregated mobility data of infected individuals only. Clearly, naively
linking mobile phone data with health records would violate privacy by
either allowing to track mobility patterns of infected individuals, leak
information on who is infected, or both. This work aims to develop a
solution that reports the aggregated mobile phone location data of in-
fected individuals while still maintaining compliance with privacy expec-
tations. To achieve privacy, we use homomorphic encryption, validation
techniques derived from zero-knowledge proofs, and differential privacy.
Our protocol’s open-source implementation can process eight million sub-
scribers in 70 minutes.
Originalspracheenglisch
Seitenumfang34
PublikationsstatusAngenommen/In Druck - 11 Juli 2022
Veranstaltung22nd Privacy Enhancing Technologies Symposium: PETS 2022 - Sydney, Australien
Dauer: 11 Juli 202215 Juli 2022
Konferenznummer: 22

Konferenz

Konferenz22nd Privacy Enhancing Technologies Symposium
KurztitelPETS 2022
Land/GebietAustralien
Zeitraum11/07/2215/07/22

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