Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks

<div><p>Intelligent transportation systems necessitate a fine-grained and accurate estimation of vehicular traffic flows across critical paths of the underlying road network. However, such statistics should be collected in a manner that does not disclose the trajectories of individual us...

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Main Author: Elmahdi Bentafat (16896405) (author)
Other Authors: M. Mazhar Rathore (16896399) (author), Spiridon Bakiras (16896408) (author)
Published: 2021
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author Elmahdi Bentafat (16896405)
author2 M. Mazhar Rathore (16896399)
Spiridon Bakiras (16896408)
author2_role author
author
author_facet Elmahdi Bentafat (16896405)
M. Mazhar Rathore (16896399)
Spiridon Bakiras (16896408)
author_role author
dc.creator.none.fl_str_mv Elmahdi Bentafat (16896405)
M. Mazhar Rathore (16896399)
Spiridon Bakiras (16896408)
dc.date.none.fl_str_mv 2021-04-01T03:00:00Z
dc.identifier.none.fl_str_mv 10.1155/2021/6619770
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Privacy-Preserving_Multipoint_Traffic_Flow_Estimation_for_Road_Networks/26940259
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Commerce, management, tourism and services
Transportation, logistics and supply chains
Information and computing sciences
Cybersecurity and privacy
Intelligent Transportation Systems (ITS)
Vehicular Traffic Flow Estimation
Privacy-Preserving Protocol
Roadside Units (RSUs)
dc.title.none.fl_str_mv Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <div><p>Intelligent transportation systems necessitate a fine-grained and accurate estimation of vehicular traffic flows across critical paths of the underlying road network. However, such statistics should be collected in a manner that does not disclose the trajectories of individual users. To this end, we introduce a privacy-preserving protocol that leverages roadside units (RSUs) to communicate with the passing vehicles, in order to construct encrypted Bloom filters stemming from random vehicle IDs that are chosen secretly by the individual vehicles. Each Bloom filter represents the set of vehicle IDs that contacted the RSU but may also be used to estimate the traffic flow between any number of RSUs. More precisely, we designed a probabilistic model that approximates multipoint traffic flows by estimating the number of common vehicles among a given set of RSUs. Through extensive simulation experiments, we demonstrate that our protocol is very accurate—with a minor deviation from the real traffic flow—and show that it reduces the estimation error by a large factor, when compared to the current state-of-the-art approaches. Furthermore, our implementation of the underlying cryptographic primitives illustrates the feasibility, practicality, and scalability of the system.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Security and Communication Networks<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1155/2021/6619770" target="_blank">https://dx.doi.org/10.1155/2021/6619770</a></p>
eu_rights_str_mv openAccess
id Manara2_9938b142de33edc2d89272346be59d78
identifier_str_mv 10.1155/2021/6619770
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/26940259
publishDate 2021
repository.mail.fl_str_mv
repository.name.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling Privacy-Preserving Multipoint Traffic Flow Estimation for Road NetworksElmahdi Bentafat (16896405)M. Mazhar Rathore (16896399)Spiridon Bakiras (16896408)Commerce, management, tourism and servicesTransportation, logistics and supply chainsInformation and computing sciencesCybersecurity and privacyIntelligent Transportation Systems (ITS)Vehicular Traffic Flow EstimationPrivacy-Preserving ProtocolRoadside Units (RSUs)<div><p>Intelligent transportation systems necessitate a fine-grained and accurate estimation of vehicular traffic flows across critical paths of the underlying road network. However, such statistics should be collected in a manner that does not disclose the trajectories of individual users. To this end, we introduce a privacy-preserving protocol that leverages roadside units (RSUs) to communicate with the passing vehicles, in order to construct encrypted Bloom filters stemming from random vehicle IDs that are chosen secretly by the individual vehicles. Each Bloom filter represents the set of vehicle IDs that contacted the RSU but may also be used to estimate the traffic flow between any number of RSUs. More precisely, we designed a probabilistic model that approximates multipoint traffic flows by estimating the number of common vehicles among a given set of RSUs. Through extensive simulation experiments, we demonstrate that our protocol is very accurate—with a minor deviation from the real traffic flow—and show that it reduces the estimation error by a large factor, when compared to the current state-of-the-art approaches. Furthermore, our implementation of the underlying cryptographic primitives illustrates the feasibility, practicality, and scalability of the system.</p><p> </p></div><h2>Other Information</h2> <p> Published in: Security and Communication Networks<br> License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1155/2021/6619770" target="_blank">https://dx.doi.org/10.1155/2021/6619770</a></p>2021-04-01T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1155/2021/6619770https://figshare.com/articles/journal_contribution/Privacy-Preserving_Multipoint_Traffic_Flow_Estimation_for_Road_Networks/26940259CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/269402592021-04-01T03:00:00Z
spellingShingle Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
Elmahdi Bentafat (16896405)
Commerce, management, tourism and services
Transportation, logistics and supply chains
Information and computing sciences
Cybersecurity and privacy
Intelligent Transportation Systems (ITS)
Vehicular Traffic Flow Estimation
Privacy-Preserving Protocol
Roadside Units (RSUs)
status_str publishedVersion
title Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
title_full Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
title_fullStr Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
title_full_unstemmed Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
title_short Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
title_sort Privacy-Preserving Multipoint Traffic Flow Estimation for Road Networks
topic Commerce, management, tourism and services
Transportation, logistics and supply chains
Information and computing sciences
Cybersecurity and privacy
Intelligent Transportation Systems (ITS)
Vehicular Traffic Flow Estimation
Privacy-Preserving Protocol
Roadside Units (RSUs)