Meeting points in ridesharing: A privacy-preserving approach

Autor: Sébastien Gambs, Ulrich Aïvodji, Marie-José Huguet, Marc-Olivier Killijian
Přispěvatelé: Équipe Tolérance aux fautes et Sûreté de Fonctionnement informatique (LAAS-TSF), Laboratoire d'analyse et d'architecture des systèmes (LAAS), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Équipe Recherche Opérationnelle, Optimisation Combinatoire et Contraintes (LAAS-ROC), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Secure Multiparty Computation
Engineering
Service (systems architecture)
Multimodal Shortest Path
Control (management)
Internet privacy
Transportation
Private Set Intersection
010501 environmental sciences
Computer security
computer.software_genre
Privacy Enhancing Technologies
01 natural sciences
[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing
[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]
11. Sustainability
0502 economics and business
0105 earth and related environmental sciences
Civil and Structural Engineering
050210 logistics & transportation
business.industry
Dynamic Ridesharing
05 social sciences
Usability
[INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO]
Flow network
Computer Science Applications
Information and Communications Technology
Automotive Engineering
Shortest path problem
Secure multi-party computation
Privacy-enhancing technologies
business
computer
Zdroj: Transportation research. Part C, Emerging technologies
Transportation research. Part C, Emerging technologies, Elsevier, 2016, 72, pp.239-253. ⟨10.1016/j.trc.2016.09.017⟩
Transportation research. Part C, Emerging technologies, 2016, 72, pp.239-253. ⟨10.1016/j.trc.2016.09.017⟩
ISSN: 0968-090X
1879-2359
Popis: International audience; Nowadays, problems of congestion in urban areas due to the massive usage of cars, last-minute travel needs and progress in information and communication technologies have fostered the rise of new transportation modes such as ridesharing. In a ridesharing service, a car owner shares empty seats of his car with other travelers. Recent ridesharing approaches help to identify interesting meeting points to improve the efficiency of the ridesharing service (i.e., the best pickup and drop-off points so that the travel cost is competitive for both driver and rider). In particular, ridesharing services, such as Blablacar or Carma, have become a good mobility alternative for users in their daily life. However, this success has come at the cost of user privacy. Indeed in current's ridesharing services, users are not in control of their own data and have to trust the ridesharing operators with the management of their data. In this paper, we aim at developing a privacy-preserving service to compute meeting points in ridesharing, such that each user remains in control of his location data. More precisely, we propose a decentralized architecture that provides strong security and privacy guarantees without sacrificing the usability of ridesharing services. In particular, our approach protects the privacy of location data of users. Following the privacy-by-design principle, we have integrated existing privacy enhancing technologies and multimodal shortest path algorithms to privately compute mutually interesting meeting points for both drivers and riders in ridesharing. In addition, we have built a prototype implementation of the proposed approach. The experiments, conducted on a real transportation network, have demonstrated that it is possible to reach a trade-off in which both the privacy and utility levels are satisfactory.
Databáze: OpenAIRE
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