Anonymized Counting of Nonstationary Wi-Fi Devices When Monitoring Crowds

Valeriu-Daniel Stanciu, Maarten R. van Steen, Ciprian Dobre, Andreas Peter

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
9 Downloads (Pure)

Abstract

Pedestrian dynamics are nowadays commonly analyzed by leveraging Wi-Fi signals sent by devices that people carry with them and captured by an infrastructure of Wi-Fi scanners. Emitting such signals is not a feature for devices of only passersby, but also for printers, smart TVs, and other devices that exhibit a stationary behavior over time, which eventually end up affecting pedestrian crowd measurements. In this paper we propose a system that accurately counts nonstationary devices sensed by scanners, separately from stationary devices, using no information other than the Wi-Fi signals captured by each scanner in isolation. As counting involves dealing with privacy-sensitive detections of people's devices, the system discards any data in the clear immediately after sensing, later working on encrypted data that it cannot decrypt in the process. The only information made available in the clear is the intended output, i.e. statistical counts of Wi-Fi devices. Our approach relies on an object, which we call comb, that maintains, under encryption, a representation of the frequency of occurrence of devices over time. Applying this comb on the detections made by a scanner enables the calculation of the separate counts. We implement the system and feed it with data from a large open-air festival, showing that accurate anonymized counting of nonstationary Wi-Fi devices is possible when dealing with real-world detections.

Original languageEnglish
Title of host publicationMSWiM '22: Proceedings of the 25th International ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems
PublisherAssociation for Computing Machinery
Pages213-222
Number of pages10
ISBN (Electronic)9781450394796
ISBN (Print)9781450394826
DOIs
Publication statusPublished - 24 Oct 2022
Event25th ACM International Conference on Modelling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM 2022 - Virtual, Online, Canada
Duration: 24 Oct 202228 Oct 2022
Conference number: 25

Publication series

NameMSWiM 2022 - Proceedings of the International Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems

Conference

Conference25th ACM International Conference on Modelling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM 2022
Abbreviated titleMSWiM 2022
Country/TerritoryCanada
CityVirtual, Online
Period24/10/2228/10/22

Keywords

  • anonymized counting
  • bloom filters
  • crowd monitoring
  • homomorphic encryption
  • nonstationary devices
  • privacy protection
  • statistical counting

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