skip to main content
10.1145/3565477.3569149acmconferencesArticle/Chapter ViewAbstractPublication PagesconextConference Proceedingsconference-collections
extended-abstract

Covid-19 contact tracing through multipath profile similarity

Published:06 December 2022Publication History

ABSTRACT

Contact tracing is a key approach to control the spread of Covid-19 and any other pandemia. Recent attempts have followed either traditional ways of tracing (e.g. patient interviews) or unreliable app-based localization solutions. The latter has raised both privacy concerns and low precision in the contact inference. In this work, we present the idea of contact tracing through the multipath profile similarity. At first, we collect Channel State Information (CSI) traces from mobile devices, and then we estimate the multipath profile. We then show that positions that are close obtain similar multipath profiles, and only this information is shared outside the local network. This result can be applied for deploying a privacy-preserving contact tracing system for healthcare authorities.

References

  1. Yu Feng, Thierry Marchal, Ted Sperry, and Hang Yi. 2020. Influence of wind and relative humidity on the social distancing effectiveness to prevent COVID-19 airborne transmission: A numerical study. Journal of aerosol science, 147, 105585.Google ScholarGoogle ScholarCross RefCross Ref
  2. Domenico Giustiniano, Giuseppe Bianchi, Andrea Conti, Stefania Bartoletti, and Nicola Blefari Melazzi. 2021. 5G and Beyond for Contact Tracing. IEEE Communications Magazine, 59, 9, 36--41. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Manikanta Kotaru, Kiran Joshi, Dinesh Bharadia, and Sachin Katti. 2015. SpotFi: Decimeter Level Localization Using WiFi. In Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication (SIGCOMM '15). ACM, London, United Kingdom, 269--282. isbn: 978-1-4503-3542-3. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Douglas J Leith and Stephen Farrell. 2020. Coronavirus contact tracing: Evaluating the potential of using bluetooth received signal strength for proximity detection. In number 4. Vol. 50. ACM New York, NY, USA, 66--74.Google ScholarGoogle Scholar
  5. Maurizio Rea, Traian Emanuel Abrudan, Domenico Giustiniano, Holger Claussen, and Veli-Matti Kolmonen. 2019. Smartphone Positioning with Radio Measurements from a Single Wifi Access Point. In Association for Computing Machinery, New York, NY, USA. isbn: 9781450369985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Joel Reardon, Álvaro Feal, Primal Wijesekera, Amit Elazari Bar On, Narseo Vallina-Rodriguez, and Serge Egelman. 2019. 50 Ways to Leak Your Data: An Exploration of Apps' Circumvention of the Android Permissions System. In 28th USENIX Security Symposium (USENIX Security 19). USENIX Association, Santa Clara, CA, (Aug. 2019), 603--620. isbn: 978-1-939133-06-9. https://www.usenix.org/conference/usenixsecurity19/presentation/reardon.Google ScholarGoogle Scholar
  7. Eric A Silva, Karen Panetta, and Sos S Agaian. 2007. Quantifying image similarity using measure of enhancement by entropy. In Mobile multimedia/image processing for military and security applications 2007. Vol. 6579. SPIE, 219--230.Google ScholarGoogle ScholarCross RefCross Ref
  8. VV Starovoytov, EE Eldarova, and Kazizat Takuadinovich Iskakov. 2020. Comparative analysis of the SSIM index and the pearson coefficient as a criterion for image similarity. Eurasian journal of mathematical and computer applications, 8, 1, 76--90.Google ScholarGoogle Scholar

Index Terms

  1. Covid-19 contact tracing through multipath profile similarity

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        CoNEXT-SW '22: Proceedings of the 3rd International CoNEXT Student Workshop
        December 2022
        50 pages
        ISBN:9781450399371
        DOI:10.1145/3565477

        Copyright © 2022 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 6 December 2022

        Check for updates

        Qualifiers

        • extended-abstract
      • Article Metrics

        • Downloads (Last 12 months)16
        • Downloads (Last 6 weeks)1

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader