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  • Conference on Lasers and Electro-Optics/Europe (CLEO/Europe 2023) and European Quantum Electronics Conference (EQEC 2023)
  • Technical Digest Series (Optica Publishing Group, 2023),
  • paper eb_p_1

Deep Learning Based TEMPEST Attacks on a Quantum Key Distribution Sender

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Abstract

While quantum key distribution (QKD) protocols are proven secure based on fundamental physical laws, side channels may allow an eavesdropper to obtain information unnoticeably. We present a profiled [1] side-channel attack using a deep convolutional neural network to analyze the classical, radio-frequency electromagnetic emissions from the electronics of a QKD sender. At a few centimeters from the device, we are able to recover virtually all information about the secret key. Furthermore, we can still observe traces of electromagnetic radiation from the device at distances of a few meters using a wideband antenna. Our methods are designed to be easily adaptable and may serve as a starting point for assessing the presence of this side channel for other devices.

© 2023 IEEE

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