  Quantum key distribution (QKD) protocols are proven secure based on
fundamental physical laws, however, the proofs consider a well-defined setting
and encoding of the sent quantum signals only. Side channels, where the encoded
quantum state is correlated with properties of other degrees of freedom of the
quantum channel, allow an eavesdropper to obtain information unnoticeably as
demonstrated in a number of hacking attacks on the quantum channel. Yet, also
classical radiation emitted by the devices may be correlated, leaking
information on the potential key, especially when combined with novel data
analysis methods.
  We here demonstrate a side-channel attack using a deep convolutional neural
network to analyze the recorded classical, radio-frequency electromagnetic
emissions. Even at a distance of a few centimeters from the electronics of a
QKD sender employing frequently used electronic components we are able to
recover virtually all information about the secret key. Yet, as shown here,
countermeasures can enable a significant reduction of both the emissions and
the amount of secret key information leaked to the attacker. Our analysis
methods are independent of the actual device and thus provide a starting point
for assessing the presence of classical side channels in QKD devices.
