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DLWIoT: Deep Learning-based Watermarking for Authorized IoT Onboarding.

Spyridon Mastorakis1, Xin Zhong1, Pei-Chi Huang1

  • 1Dept. of Computer Science, University of Nebraska Omaha.

IEEE Consumer Communications and Networking Conference. IEEE Consumer Communications and Networking Conference
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

Unauthorized access to IoT devices is a growing concern. A new Deep Learning-based Watermarking for authorized IoT onboarding (DLWIoT) framework uses image watermarking to secure device access for authorized users only.

Keywords:
Internet of Things (IoT)IoT onboardingdeep learningwatermarking

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Area of Science:

  • Cybersecurity
  • Internet of Things (IoT)
  • Deep Learning

Background:

  • Increasing numbers of IoT devices amplify security risks.
  • Current IoT onboarding methods (QR codes, PINs) lack robust protection against unauthorized access and tampering.
  • Physical access to devices allows unauthorized onboarding and potential malware installation.

Purpose of the Study:

  • To present a novel framework, DLWIoT, for secure and authorized IoT device onboarding.
  • To develop a robust, automated image watermarking scheme using deep neural networks for IoT security.
  • To enable IoT onboarding exclusively for authorized users by embedding credentials into carrier images.

Main Methods:

  • Development of a Deep Learning-based Watermarking for authorized IoT onboarding (DLWIoT) framework.
  • Implementation of a deep neural network-based automated image watermarking scheme.
  • Embedding user credentials into carrier images, such as QR codes on IoT devices.

Main Results:

  • Experimental validation of the DLWIoT framework's feasibility.
  • Demonstration of secure IoT onboarding exclusively for authorized users.
  • Achieved efficient onboarding times for authorized users within 2.5-3 seconds.

Conclusions:

  • DLWIoT provides a robust solution to secure IoT device onboarding against unauthorized access.
  • The deep learning-based watermarking approach enhances security without compromising onboarding speed.
  • DLWIoT effectively addresses the critical need for authorized access in the expanding IoT ecosystem.