  Due to an increase in the availability of cheap off-the-shelf radio hardware,
spoofing and replay attacks on satellite ground systems have become more
accessible than ever. This is particularly a problem for legacy systems, many
of which do not offer cryptographic security and cannot be patched to support
novel security measures.
  In this paper we explore radio transmitter fingerprinting in satellite
systems. We introduce the SatIQ system, proposing novel techniques for
authenticating transmissions using characteristics of transmitter hardware
expressed as impairments on the downlinked signal. We look in particular at
high sample rate fingerprinting, making fingerprints difficult to forge without
similarly high sample rate transmitting hardware, thus raising the budget for
attacks. We also examine the difficulty of this approach with high levels of
atmospheric noise and multipath scattering, and analyze potential solutions to
this problem.
  We focus on the Iridium satellite constellation, for which we collected
1705202 messages at a sample rate of 25 MS/s. We use this data to train a
fingerprinting model consisting of an autoencoder combined with a Siamese
neural network, enabling the model to learn an efficient encoding of message
headers that preserves identifying information.
  We demonstrate the system's robustness under attack by replaying messages
using a Software-Defined Radio, achieving an Equal Error Rate of 0.120, and ROC
AUC of 0.946. Finally, we analyze its stability over time by introducing a time
gap between training and testing data, and its extensibility by introducing new
transmitters which have not been seen before. We conclude that our techniques
are useful for building systems that are stable over time, can be used
immediately with new transmitters without retraining, and provide robustness
against spoofing and replay by raising the required budget for attacks.
