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Machine Learning Techniques for Recognizing IoT Devices

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New Trends in Computer Technologies and Applications (ICS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1013))

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Abstract

Now Internet of Things is growing fast and presents huge opportunities for the industry, the users, and the hackers. IoT service providers may face challenges from IoT devices which are developed with software and hardware originally designed for mobile computing and traditional computer environments. Thus the first line of security defense of IoT service providers is identification of IoT devices and try to analyze their behaviors before allowing them to use the service. In this work, we propose to use machine learning techniques to identify the IoT devices. We also report experiment to explain the performance and potential of our techniques.

The work is supported by (1) project “IoT Testing Service Platform” by the Cybersecurity Technology Institute, Institute for Information Industry, 2018, (2) project “Coverage Testing Technology based on Game Theory” by Research Center for Information Technology Innovation, Academia Sinica, 2018, and (3) project “Cloud Client-Server Computing of Intelligent Test Service” (MOST 107-2221-E-002-037-MY3) by Ministry of Science and Technology.

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Notes

  1. 1.

    https://danielmiessler.com/study/shodan/.

  2. 2.

    https://nmap.org/.

  3. 3.

    https://www.iplocation.net/alexa-traffic-rank.

  4. 4.

    http://www.geoip.co.uk/.

  5. 5.

    https://en.wikipedia.org/wiki/Firebase.

  6. 6.

    https://en.wikipedia.org/wiki/Scapy.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC

    Yu Chien Lin & Farn Wang

Authors
  1. Yu Chien Lin
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  2. Farn Wang
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Corresponding author

Correspondence to Yu Chien Lin .

Editor information

Editors and Affiliations

  1. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chuan-Yu Chang

  2. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chien-Chou Lin

  3. Southern Taiwan University of Science and Technology, Tainan, Taiwan

    Horng-Horng Lin

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Lin, Y.C., Wang, F. (2019). Machine Learning Techniques for Recognizing IoT Devices. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_74

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  • DOI: https://doi.org/10.1007/978-981-13-9190-3_74

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9189-7

  • Online ISBN: 978-981-13-9190-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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