SATversary: Adversarial Attacks on Satellite Fingerprinting

• URL: http://arxiv.org/abs/2506.06119v1
• Date: Fri, 06 Jun 2025 14:27:19 GMT
• Title: SATversary: Adversarial Attacks on Satellite Fingerprinting
• Authors: Joshua Smailes, Sebastian Köhler, Simon Birnbach, Martin Strohmeier, Ivan Martinovic,
• Abstract summary: transmitter fingerprinting provides mechanisms by which communication can be authenticated.<n>We show that an optimized jamming signal can cause a 50% error rate with attacker-to-victim ratios as low as -30dB.<n>We also present a data poisoning attack, enabling persistent message spoofing by altering the data used to authenticate incoming messages to include the attacker's transmitter.
• Score: 14.683336638975762
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As satellite systems become increasingly vulnerable to physical layer attacks via SDRs, novel countermeasures are being developed to protect critical systems, particularly those lacking cryptographic protection, or those which cannot be upgraded to support modern cryptography. Among these is transmitter fingerprinting, which provides mechanisms by which communication can be authenticated by looking at characteristics of the transmitter, expressed as impairments on the signal. Previous works show that fingerprinting can be used to classify satellite transmitters, or authenticate them against SDR-equipped attackers under simple replay scenarios. In this paper we build upon this by looking at attacks directly targeting the fingerprinting system, with an attacker optimizing for maximum impact in jamming, spoofing, and dataset poisoning attacks, and demonstrate these attacks on the SatIQ system designed to authenticate Iridium transmitters. We show that an optimized jamming signal can cause a 50% error rate with attacker-to-victim ratios as low as -30dB (far less power than traditional jamming) and demonstrate successful identity forgery during spoofing attacks, with an attacker successfully removing their own transmitter's fingerprint from messages. We also present a data poisoning attack, enabling persistent message spoofing by altering the data used to authenticate incoming messages to include the fingerprint of the attacker's transmitter. Finally, we show that our model trained to optimize spoofing attacks can also be used to detect spoofing and replay attacks, even when it has never seen the attacker's transmitter before. Furthermore, this technique works even when the training dataset includes only a single transmitter, enabling fingerprinting to be used to protect small constellations and even individual satellites, providing additional protection where it is needed the most.

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