A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Ikram Ullah, Munam Ali Shah, Abid Khan, Carsten Maple, Abdul Waheed, Gwnaggil Jeon
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	anonymity formal modeling location privacy mix context pseudonyms traceability Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/6b69fc51565e444881af9aa6a926d092
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6b69fc51565e444881af9aa6a926d092
record_format	dspace
spelling	oai:doaj.org-article:6b69fc51565e444881af9aa6a926d0922021-11-25T19:01:49ZA Distributed Mix-Context-Based Method for Location Privacy in Road Networks10.3390/su1322125132071-1050https://doaj.org/article/6b69fc51565e444881af9aa6a926d0922021-11-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/22/12513https://doaj.org/toc/2071-1050Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications.Ikram UllahMunam Ali ShahAbid KhanCarsten MapleAbdul WaheedGwnaggil JeonMDPI AGarticleanonymityformal modelinglocation privacymix contextpseudonymstraceabilityEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12513, p 12513 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	anonymity formal modeling location privacy mix context pseudonyms traceability Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	anonymity formal modeling location privacy mix context pseudonyms traceability Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Ikram Ullah Munam Ali Shah Abid Khan Carsten Maple Abdul Waheed Gwnaggil Jeon A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
description	Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications.
format	article
author	Ikram Ullah Munam Ali Shah Abid Khan Carsten Maple Abdul Waheed Gwnaggil Jeon
author_facet	Ikram Ullah Munam Ali Shah Abid Khan Carsten Maple Abdul Waheed Gwnaggil Jeon
author_sort	Ikram Ullah
title	A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
title_short	A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
title_full	A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
title_fullStr	A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
title_full_unstemmed	A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
title_sort	distributed mix-context-based method for location privacy in road networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/6b69fc51565e444881af9aa6a926d092
work_keys_str_mv	AT ikramullah adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT munamalishah adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT abidkhan adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT carstenmaple adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT abdulwaheed adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT gwnaggiljeon adistributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT ikramullah distributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT munamalishah distributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT abidkhan distributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT carstenmaple distributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT abdulwaheed distributedmixcontextbasedmethodforlocationprivacyinroadnetworks AT gwnaggiljeon distributedmixcontextbasedmethodforlocationprivacyinroadnetworks
_version_	1718410407529414656

A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

Ejemplares similares