Neural Network Detection and Identification of Electronic Devices Based on Their Unintended Emissions
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Abstract
Electromagnetic emissions were measured from several radio receivers to demonstrate the possibility of detecting and identifying these devices based on their unintended emissions. Radiated fields from the different radio receivers have unique characteristics that can be used to identify these devices by analyzing time-frequency plots of measured radiation. A neural network was also developed for automated device detection.
This paper has been withdrawn.
