Understanding the protection of privacy when counting subway travelers through anonymization

Shafaeipour, N., Stanciu, V.-D., van Steen, M. and Wang, M. (2024) Understanding the protection of privacy when counting subway travelers through anonymization. Computers, Environment and Urban Systems, 110, 102091. (doi: 10.1016/j.compenvurbsys.2024.102091)

Abstract

Public transportation, especially in large cities, is critical for livability. Counting passengers as they travel between stations is crucial to establishing and maintaining effective transportation systems. Various information and communication technologies, such as GPS, Bluetooth, and Wi-Fi, have been used to measure people's movements automatically. Regarding public transportation applications, the automated fare collection (AFC) system has been widely adopted as a convenient method for measuring passengers, mainly because it is relatively easy to identify card owners uniquely and, as such, the movements of their card holders. However, there are serious concerns regarding privacy infringements when deploying such technologies, to the extent that Europe's General Data Protection Regulation has forbidden straightforward deployment for measuring pedestrian dynamics unless explicit consent has been provided. As a result, privacy-preservation techniques (e.g., anonymization) must be used when deploying such systems. Against this backdrop, we investigate to what extent a recently developed anonymization technique, known as detection k-anonymity, can be adapted to count public transportation travelers while preserving privacy. In the case study, we tested our methods with data from Beijing subway trips. Results show different scenarios when detection k-anonymity can be effectively applied and when it cannot. Due to the complicated relationship between the detection k-anonymity parameters, setting the proper parameter values can be difficult, leading to inaccurate results. Furthermore, through detection k-anonymity, it is possible to count travelers between two locations with high accuracy. However, counting travelers from more than two locations leads to more inaccurate results.

• Item Type: Articles
• Additional Information: This research was supported in part by the Dutch Research Council (NWO), "Measuring pedestrian dynamics: doing it the right way" (Grant No. 410.19.002).
• Keywords: K-anonymity, travelers, privacy preservation, general data protection regulation, public transportation.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Wang, Dr Mingshu

Creator Roles

Wang, M.: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review and editing

• Authors: Shafaeipour, N., Stanciu, V.-D., van Steen, M., and Wang, M.
• College/School: College of Science and Engineering > School of Geographical and Earth Sciences
• Journal Name: Computers, Environment and Urban Systems
• Publisher: Elsevier
• ISSN: 0198-9715
• ISSN (Online): 1873-7587
• Published Online: 14 March 2024
• Copyright Holders: Copyright © 2024 The Authors
• First Published: First published in Computers, Environment and Urban Systems 110: 102091
• Publisher Policy: Reproduced under a Creative Commons License