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Fingerprinting the IoT

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Radio frequency fingerprinting is a method of identifying devices by exploiting hardware variations that arise during the manufacturing process, which result in unique features in the radio waves the device transmits.

Credit: Carnegie Mellon University College of Engineering

Carnegie Mellon University (CMU) researchers strengthened the security of Internet of Things (IoT) devices by making them more resilient against exploitation through their development of radio -requency fingerprinting (RFF).

RFF can be used to identify specific IoT devices by detecting hardware variations that produce unique radio wave signatures.

CMU's Jiachen Xu used power amplifiers to foil RFF exploits by changing the IoT signal's features, and a convolutional neural network classified incoming signals as safe or unsafe by assessing the RFF in the processed signal.

The researchers also proved Bayesian neural networks could identify and classify RFF quickly and accurately, without requiring excessive computational power.

From Carnegie Mellon University College of Engineering News
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA


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