Localization from Activity Sensor Data: poster abstract

Franz Papst, Naomi Stricker, Olga Saukh

Research output: Contribution to conferencePosterpeer-review

Abstract

In this work, we show that sensor data may leak a sensor’s location even if the latter is not explicitly included in the data set. The sensors are localized by linking sensor data, in particular activity data, with publicly available environmental data such as weather data. We show that using a linkage attack a cow can be localized within an entire country with an average accuracy of up to 32.6 km solely from activity traces recorded with a tracker in the cow’s stomach.
Original languageEnglish
Pages703-704
Number of pages2
DOIs
Publication statusPublished - 16 Nov 2020
Event18th ACM Conference on Embedded Networked Sensor Systems: SenSys 2020 - Online, Virtual, Yokohama, Japan
Duration: 16 Nov 202019 Nov 2020
http://sensys.acm.org/2020/
http://sensys.acm.org/2020/index.html

Conference

Conference18th ACM Conference on Embedded Networked Sensor Systems
Abbreviated titleSenSys
Country/TerritoryJapan
CityVirtual, Yokohama
Period16/11/2019/11/20
Internet address

Keywords

  • localization
  • location privacy
  • sensor data

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Computer Networks and Communications

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