Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

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

doi:10.56553/popets-2022-0132

Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently 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 expectations. 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.

Original language	English
Title of host publication	Proceedings on Privacy Enhancing Technologies 2022
Pages	768-788
Number of pages	34
Volume	4
DOIs	https://doi.org/10.56553/popets-2022-0132
Publication status	Published - 11 Jul 2022
Event	22nd Privacy Enhancing Technologies Symposium: PETS 2022 - Sydney, Australia Duration: 11 Jul 2022 → 15 Jul 2022 Conference number: 22

Conference

Conference	22nd Privacy Enhancing Technologies Symposium
Abbreviated title	PETS 2022
Country/Territory	Australia
Period	11/07/22 → 15/07/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.56553/popets-2022-0132Licence: CC BY-NC-ND 3.0

Cite this

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title = "Privately Connecting Mobility to Infectious Diseases via Applied Cryptography",

abstract = "Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently the spread of infected diseases [74]. While prior studies have exclusively relied on a mobile network operator{\textquoteright}s subscribers{\textquoteright} 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 expectations. To achieve privacy, we use homomorphic encryption, validation techniques derived from zero-knowledge proofs, and differential privacy.Our protocol{\textquoteright}s open-source implementation can process eight million sub-scribers in 70 minutes.",

author = "Alexandros Bampoulidis and Alessandro Bruni and Lukas Helminger and Daniel Kales and Christian Rechberger and Roman Walch",

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AU - Bampoulidis, Alexandros

AU - Bruni, Alessandro

AU - Helminger, Lukas

AU - Kales, Daniel

AU - Rechberger, Christian

AU - Walch, Roman

N1 - Conference code: 22

PY - 2022/7/11

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AB - Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently 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 expectations. 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.

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Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

Abstract

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

DDAI - Explainable, Verifiable and Privacy-Preserving Data-Driven AI

EU - KRAKEN - Brokerage and market platform for personal data

Cite this

Privately Connecting Mobility to Infectious Diseases via Applied Cryptography

Abstract

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Projects

DDAI - Explainable, Verifiable and Privacy-Preserving Data-Driven AI

EU - KRAKEN - Brokerage and market platform for personal data

Cite this