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TOPPool: Time-aware Optimized Privacy-Preserving Ridesharing

Pagnin, Elena LU orcid ; Gunnarsson, Gunnar ; Talebi, Pedram ; Orlandi, Claudio and Sabelfeld, Andrei (2019) In Proceedings on Privacy Enhancing Technologies 2019(4).
Abstract
Ridesharing is revolutionizing the transportation industry in many countries. Yet, the state of the art is based on heavily centralized services and platforms, where the service providers have full possession of the users’ location data. Recently, researchers have started addressing the challenge of enabling privacy-preserving ridesharing. The initial proposals, however, have shortcomings, as some rely on a central party, some incur high performance penalties, and most do not consider time preferences for ridesharing. TOPPool encompasses ridesharing based on the proximity of end-points of a ride as well as partial itinerary... (More)
Ridesharing is revolutionizing the transportation industry in many countries. Yet, the state of the art is based on heavily centralized services and platforms, where the service providers have full possession of the users’ location data. Recently, researchers have started addressing the challenge of enabling privacy-preserving ridesharing. The initial proposals, however, have shortcomings, as some rely on a central party, some incur high performance penalties, and most do not consider time preferences for ridesharing. TOPPool encompasses ridesharing based on the proximity of end-points of a ride as well as partial itinerary overlaps. To achieve the latter, we propose a simple yet powerful reduction to a private set intersection on trips represented as sets of consecutive road segments. We show that TOPPool includes time preferences while preserving privacy and without relying on a third party. We evaluate our approach on real-world data from the New York’s Taxi & Limousine Commission. Our experiments demonstrate that TOPPool is superior in performance over the prior work: our intersection-based itinerary matching runs in less than 0.3 seconds for reasonable trip length, in contrast, on the same set of trips prior work takes up to 10 hours. (Less)
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publishing date
type
Contribution to journal
publication status
published
subject
in
Proceedings on Privacy Enhancing Technologies
volume
2019
issue
4
ISSN
2299-0984
DOI
10.2478/popets-2019-0060
language
English
LU publication?
no
id
0b519079-e8ff-4897-9810-f180a06772b9
date added to LUP
2021-01-26 15:56:30
date last changed
2021-01-27 08:28:05
@article{0b519079-e8ff-4897-9810-f180a06772b9,
  abstract     = {{Ridesharing is revolutionizing the transportation industry in many countries. Yet, the state of the art is based on heavily centralized services and platforms, where the service providers have full possession of the users’ location data. Recently, researchers have started addressing the challenge of enabling <em style="box-sizing: inherit; color: rgb(60, 60, 60); font-family: Montserrat, sans-serif; font-size: 16px;">privacy-preserving ridesharing</em>. The initial proposals, however, have shortcomings, as some rely on a central party, some incur high performance penalties, and most do not consider time preferences for ridesharing. TOPPool encompasses ridesharing based on the proximity of end-points of a ride as well as partial itinerary overlaps. To achieve the latter, we propose a simple yet powerful reduction to a private set intersection on trips represented as sets of consecutive road segments. We show that TOPPool includes time preferences while preserving privacy and without relying on a third party. We evaluate our approach on real-world data from the New York’s Taxi &amp; Limousine Commission. Our experiments demonstrate that TOPPool is superior in performance over the prior work: our intersection-based itinerary matching runs in less than 0.3 seconds for reasonable trip length, in contrast, on the same set of trips prior work takes up to 10 hours.}},
  author       = {{Pagnin, Elena and Gunnarsson, Gunnar and Talebi, Pedram and Orlandi, Claudio and Sabelfeld, Andrei}},
  issn         = {{2299-0984}},
  language     = {{eng}},
  number       = {{4}},
  series       = {{Proceedings on Privacy Enhancing Technologies}},
  title        = {{TOPPool: Time-aware Optimized Privacy-Preserving Ridesharing}},
  url          = {{http://dx.doi.org/10.2478/popets-2019-0060}},
  doi          = {{10.2478/popets-2019-0060}},
  volume       = {{2019}},
  year         = {{2019}},
}