skip to main content
10.1145/3411498.3419962acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
short-paper

Privacy in the Mobile World: An Analysis of Bluetooth Scan Traces

Published: 09 November 2020 Publication History

Abstract

Bluetooth-enabled smartphones, wearable devices, as well as consumer electronics devices, are pervasive nowadays. Due to the low power consumption of Bluetooth hardware, users often leave Bluetooth enabled on their personal devices all the time. We find that even though the devices themselves may be protected against unauthorized connections, neighboring Bluetooth signals may still leak personal information. More specifically, a malicious smartphone application can easily obtain permission to perform Bluetooth scanning and then build a temporal trace of the number of active Bluetooth devices in the vicinity of a user. By collecting and analyzing data from 49 smartphone users over two weeks, we found that traces from different devices have little overlap and can, therefore, be used to identify a device with high likelihood. Moreover, Bluetooth advertisements from nearby devices can reveal what products the user may own making her susceptible to targeted advertisements. By comparing Bluetooth traces from multiple devices, the adversary can learn a user's location even if she does not give explicit permission to share her location. We also analyzed a public Bluetooth dataset to find similarities and differences with the conclusions drawn from our dataset. Our dataset has been publicly released for the scientific community.

References

[1]
2019. Two Weeks Bluetooth Low Energy Dataset. https://github.com/ purdue-dcsl/bluetooth-trace
[2]
Wahhab Albazrqaoe, Jun Huang, and Guoliang Xing. 2016. Practical bluetooth traffic sniffing: Systems and privacy implications. In Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services. ACM, 333--345.
[3]
Inc. Bluetooth SIG. 2015. Bluetooth Technology Protecting Your Privacy. https://www.bluetooth.com/blog/bluetooth-technology-protecting-your-privacy/
[4]
William S Cleveland. 1979. Robust locally weighted regression and smoothing scatterplots. Journal of the American statistical association, Vol. 74, 368 (1979), 829--836.
[5]
Aveek K Das, Parth H Pathak, Chen-Nee Chuah, and Prasant Mohapatra. 2016. Uncovering privacy leakage in ble network traffic of wearable fitness trackers. In Proceedings of the 17th International Workshop on Mobile Computing Systems and Applications. ACM, 99--104.
[6]
Kassem Fawaz, Kyu-Han Kim, and Kang G Shin. 2016. Protecting Privacy of {BLE} Device Users. In 25th {USENIX} Security Symposium ({USENIX} Security 16). 1205--1221.
[7]
Inc Fitbit. 2019. Fitbit. https://play.google.com/store/apps/details?id=com.fitbit.FitbitMobile&hl=en_US
[8]
Adriano Galati and Chris Greenhalgh. 2013. CRAWDAD dataset nottingham/mall (v. 2013-02-05). Downloaded from https://crawdad.org/nottingham/mall/20130205. https://doi.org/10.15783/C7D30D
[9]
Taher Issoufaly and Pierre Ugo Tournoux. 2017. BLEB: Bluetooth Low Energy Botnet for large scale individual tracking. In 2017 1st International Conference on Next Generation Computing Applications (NextComp). IEEE, 115--120.
[10]
Aleksandra Korolova and Vinod Sharma. 2018. Cross-App Tracking via Nearby Bluetooth Low Energy Devices. In Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy. ACM, 43--52.
[11]
Joshua S Richman, Douglas E Lake, and J Randall Moorman. 2004. Sample entropy. In Methods in enzymology. Vol. 384. Elsevier, 172--184.
[12]
Pallavi Sivakumaran and Jorge Blasco. 2019. A Study of the Feasibility of Co-located App Attacks against {BLE} and a Large-Scale Analysis of the Current Application-Layer Security Landscape. In 28th {USENIX} Security Symposium ({USENIX} Security 19). 1--18.
[13]
Fenghao Xu, Wenrui Diao, Zhou Li, Jiongyi Chen, and Kehuan Zhang. 2019. BadBluetooth: Breaking Android Security Mechanisms via Malicious Bluetooth Peripherals. In NDSS.

Cited By

View all
  • (2024)SoK: The Long Journey of Exploiting and Defending the Legacy of King Harald Bluetooth2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00023(2847-228066)Online publication date: 19-May-2024
  • (2020)(De)randomized smoothing for certifiable defense against patch attacksProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496266(6465-6475)Online publication date: 6-Dec-2020

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
CPSIOTSEC'20: Proceedings of the 2020 Joint Workshop on CPS&IoT Security and Privacy
November 2020
99 pages
ISBN:9781450380874
DOI:10.1145/3411498
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 November 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. bluetooth
  2. privacy
  3. time series analysis

Qualifiers

  • Short-paper

Conference

CCS '20
Sponsor:

Upcoming Conference

CCS '25

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)11
  • Downloads (Last 6 weeks)0
Reflects downloads up to 05 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2024)SoK: The Long Journey of Exploiting and Defending the Legacy of King Harald Bluetooth2024 IEEE Symposium on Security and Privacy (SP)10.1109/SP54263.2024.00023(2847-228066)Online publication date: 19-May-2024
  • (2020)(De)randomized smoothing for certifiable defense against patch attacksProceedings of the 34th International Conference on Neural Information Processing Systems10.5555/3495724.3496266(6465-6475)Online publication date: 6-Dec-2020

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media