skip to main content
10.1145/3508398.3519356acmconferencesArticle/Chapter ViewAbstractPublication PagescodaspyConference Proceedingsconference-collections
poster

Demystifying Video Traffic from IoT (Spy) Camera using Undecrypted Network Traffic

Authors Info & Claims
Published:15 April 2022Publication History

ABSTRACT

Video traffic can create significant privacy and security threats to an organization or a smart home. Integration of IoT cameras has increased this problem manifold especially when there is no clear distinction among the protocols that can be used in IoT cameras and traditional video streaming or sharing applications. In this paper, we initiate a study on distinguishing video traffic in IoT cameras from that in video conferencing or sharing applications. We have used three IoT cameras, four video conferencing applications and two video sharing platforms to collect network traffic at network and above layers. We found a number of protocols like Real-time Transport Protocol, QUIC protocol, UDT protocol and TLS protocols that are used for transferring video traffic in these applications. We found that the protocols that carry IoT camera traffic have significantly different characteristics compared to that in video conferencing and sharing applications, e.g., in terms of video codec.

Skip Supplemental Material Section

Supplemental Material

CODASPY2022_codasp09.mp4

mp4

15.4 MB

References

  1. ESOMER. Smart camera market size and forecast. https://www.verifiedmarketresearch.com/product/global-smart-camera-market/, 2021.Google ScholarGoogle Scholar
  2. Inc Global Market Insights. Video conferencing market to exhibit 19% growth through 2026. https://www.globenewswire.com/, 2021.Google ScholarGoogle Scholar
  3. YIWU LEIXUN COMPANY. Enem bulb camera. https://www.amazon.in/Camera-Hidden-Security-Communication-Warranty/dp/B0848NQXRV, 2020.Google ScholarGoogle Scholar
  4. E. P. Freire, A. Ziviani, and R. M. Salles. Detecting skype flows in web traffic. In NOMS 2008 - 2008 IEEE Network Operations and Management Symposium, pages 89--96, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  5. M M. Sha, T Manesh, and S. M. Abd Elatty. Forensic framework for skype communication. In Intelligent Systems Technologies and Applications, pages 197--211. Springer, 2016.Google ScholarGoogle Scholar
  6. Juan Wang, Shirong Hao, Ru Wen, Boxian Zhang, Liqiang Zhang, Hongxin Hu, and Rongxing Lu. Iot-praetor: Undesired behaviors detection for iot devices. IEEE Internet of Things Journal, 8(2):927--940, 2020.Google ScholarGoogle ScholarCross RefCross Ref
  7. D. Alharbi R.and Aspinall. An iot analysis framework: An investigation of iot smart cameras' vulnerabilities. 2018.Google ScholarGoogle Scholar
  8. Hugo Fonseca, Tiago Cruz, Paulo Sim oes, Edmundo Monteiro, José Silva, Pedro Gomes, and Nuno Centeio. A comparison of classification techniques for detection of voip traffic. In 2014 Eighth International Conference on Next Generation Mobile Apps, Services and Technologies, pages 117--122. IEEE, 2014.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Demystifying Video Traffic from IoT (Spy) Camera using Undecrypted Network Traffic

    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
      CODASPY '22: Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy
      April 2022
      392 pages
      ISBN:9781450392204
      DOI:10.1145/3508398

      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: 15 April 2022

      Check for updates

      Qualifiers

      • poster

      Acceptance Rates

      Overall Acceptance Rate149of789submissions,19%

      Upcoming Conference

      CODASPY '24
    • Article Metrics

      • Downloads (Last 12 months)32
      • Downloads (Last 6 weeks)2

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader