How to Count Travelers Without Tracking Them Between Locations

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Abstract

Understanding the movements of travelers is essential for sustainable city planning, and unique identifiers from wireless network access points or smart card check-ins provide the necessary information to count and track individuals as they move between locations. Nevertheless, it is challenging to deal with such uniquely identifying data in a way that does not violate the privacy of individuals. Even though several protection techniques have been proposed, the data they produce can often still be used to track down specific individuals when combined with other external information. To address this issue, we use a novel method based on encrypted Bloom filters. These probabilistic data structures are used to represent sets while preserving privacy under strong cryptographic guarantees. In our setup, encrypted Bloom filters offer statistical counts of travelers as the only accessible information. However, the probabilistic nature of Bloom filters may lead to undercounting or overcounting of travelers, affecting accuracy. We explain our privacy-preserving method and examine the accuracy of counting the number of travelers as they move between locations. To accomplish this, we used a simulated subway dataset. The results indicate that it is possible to achieve highly accurate counting while ensuring that data cannot be used to trace and identify an individual.

Original languageEnglish
Title of host publication12th International Conference on Geographic Information Science, GIScience 2023
EditorsRoger Beecham, Jed A. Long, Dianna Smith, Qunshan Zhao, Sarah Wise
PublisherDagstuhl
ISBN (Electronic)9783959772884
DOIs
Publication statusPublished - Sept 2023
Event12th International Conference on Geographic Information Science, GIScience 2023 - Leeds, United Kingdom
Duration: 12 Sept 202315 Sept 2023
Conference number: 12
https://giscience2023.github.io/index.html

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume277
ISSN (Print)1868-8969

Conference

Conference12th International Conference on Geographic Information Science, GIScience 2023
Abbreviated titleGIScience 2023
Country/TerritoryUnited Kingdom
CityLeeds
Period12/09/2315/09/23
Internet address

Keywords

  • encrypted Bloom filters
  • Privacy preservation
  • subway networks
  • traveler counting

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