DeepAI AI Chat
Log In Sign Up

DLWIoT: Deep Learning-based Watermarking for Authorized IoT Onboarding

by   Spyridon Mastorakis, et al.

The onboarding of IoT devices by authorized users constitutes both a challenge and a necessity in a world, where the number of IoT devices and the tampering attacks against them continuously increase. Commonly used onboarding techniques today include the use of QR codes, pin codes, or serial numbers. These techniques typically do not protect against unauthorized device access-a QR code is physically printed on the device, while a pin code may be included in the device packaging. As a result, any entity that has physical access to a device can onboard it onto their network and, potentially, tamper it (e.g.,install malware on the device). To address this problem, in this paper, we present a framework, called Deep Learning-based Watermarking for authorized IoT onboarding (DLWIoT), featuring a robust and fully automated image watermarking scheme based on deep neural networks. DLWIoT embeds user credentials into carrier images (e.g., QR codes printed on IoT devices), thus enables IoT onboarding only by authorized users. Our experimental results demonstrate the feasibility of DLWIoT, indicating that authorized users can onboard IoT devices with DLWIoT within 2.5-3sec.


page 1

page 2


IoT2Vec: Identification of Similar IoT Devices via Activity Footprints

We consider a smart home or smart office environment with a number of Io...

Privacy-from-Birth: Protecting Sensed Data from Malicious Sensors with VERSA

There are many well-known techniques to secure sensed data in IoT/CPS sy...

IoT Device Identification Based on Network Communication Analysis Using Deep Learning

Attack vectors for adversaries have increased in organizations because o...

IoT-REX: A Secure Remote-Control System for IoT Devices from Centralized Multi-Designated Verifier Signatures

IoT technology has been developing rapidly, while at the same time, it r...

On the Analysis of MUD-Files' Interactions, Conflicts, and Configuration Requirements Before Deployment

Manufacturer Usage Description (MUD) is an Internet Engineering Task For...

Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement

The rapid uptake of intelligent applications is pushing deep learning (D...

A Tagging Solution to Discover IoT Devices in Apartments

The number of IoT devices in smart homes is increasing. This broad adopt...