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A secure location-based alert system with tunable privacy-performance trade-off

Monitoring location updates from mobile users has important applications in many areas, ranging from public health (e.g., COVID-19 contact tracing) and national security to social networks and advertising. However, sensitive information can be derived from movement patterns, thus protecting the priv...

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Detalles Bibliográficos
Autores principales: Ghinita, Gabriel, Nguyen, Kien, Maruseac, Mihai, Shahabi, Cyrus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297513/
https://www.ncbi.nlm.nih.gov/pubmed/32837253
http://dx.doi.org/10.1007/s10707-020-00410-1
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author Ghinita, Gabriel
Nguyen, Kien
Maruseac, Mihai
Shahabi, Cyrus
author_facet Ghinita, Gabriel
Nguyen, Kien
Maruseac, Mihai
Shahabi, Cyrus
author_sort Ghinita, Gabriel
collection PubMed
description Monitoring location updates from mobile users has important applications in many areas, ranging from public health (e.g., COVID-19 contact tracing) and national security to social networks and advertising. However, sensitive information can be derived from movement patterns, thus protecting the privacy of mobile users is a major concern. Users may only be willing to disclose their locations when some condition is met, for instance in proximity of a disaster area or an event of interest. Currently, such functionality can be achieved using searchable encryption. Such cryptographic primitives provide provable guarantees for privacy, and allow decryption only when the location satisfies some predicate. Nevertheless, they rely on expensive pairing-based cryptography (PBC), of which direct application to the domain of location updates leads to impractical solutions. We propose secure and efficient techniques for private processing of location updates that complement the use of PBC and lead to significant gains in performance by reducing the amount of required pairing operations. We implement two optimizations that further improve performance: materialization of results to expensive mathematical operations, and parallelization. We also propose an heuristic that brings down the computational overhead through enlarging an alert zone by a small factor (given as system parameter), therefore trading off a small and controlled amount of privacy for significant performance gains. Extensive experimental results show that the proposed techniques significantly improve performance compared to the baseline, and reduce the searchable encryption overhead to a level that is practical in a computing environment with reasonable resources, such as the cloud.
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spelling pubmed-72975132020-06-17 A secure location-based alert system with tunable privacy-performance trade-off Ghinita, Gabriel Nguyen, Kien Maruseac, Mihai Shahabi, Cyrus Geoinformatica Article Monitoring location updates from mobile users has important applications in many areas, ranging from public health (e.g., COVID-19 contact tracing) and national security to social networks and advertising. However, sensitive information can be derived from movement patterns, thus protecting the privacy of mobile users is a major concern. Users may only be willing to disclose their locations when some condition is met, for instance in proximity of a disaster area or an event of interest. Currently, such functionality can be achieved using searchable encryption. Such cryptographic primitives provide provable guarantees for privacy, and allow decryption only when the location satisfies some predicate. Nevertheless, they rely on expensive pairing-based cryptography (PBC), of which direct application to the domain of location updates leads to impractical solutions. We propose secure and efficient techniques for private processing of location updates that complement the use of PBC and lead to significant gains in performance by reducing the amount of required pairing operations. We implement two optimizations that further improve performance: materialization of results to expensive mathematical operations, and parallelization. We also propose an heuristic that brings down the computational overhead through enlarging an alert zone by a small factor (given as system parameter), therefore trading off a small and controlled amount of privacy for significant performance gains. Extensive experimental results show that the proposed techniques significantly improve performance compared to the baseline, and reduce the searchable encryption overhead to a level that is practical in a computing environment with reasonable resources, such as the cloud. Springer US 2020-06-16 2020 /pmc/articles/PMC7297513/ /pubmed/32837253 http://dx.doi.org/10.1007/s10707-020-00410-1 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Ghinita, Gabriel
Nguyen, Kien
Maruseac, Mihai
Shahabi, Cyrus
A secure location-based alert system with tunable privacy-performance trade-off
title A secure location-based alert system with tunable privacy-performance trade-off
title_full A secure location-based alert system with tunable privacy-performance trade-off
title_fullStr A secure location-based alert system with tunable privacy-performance trade-off
title_full_unstemmed A secure location-based alert system with tunable privacy-performance trade-off
title_short A secure location-based alert system with tunable privacy-performance trade-off
title_sort secure location-based alert system with tunable privacy-performance trade-off
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297513/
https://www.ncbi.nlm.nih.gov/pubmed/32837253
http://dx.doi.org/10.1007/s10707-020-00410-1
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