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.

翻译：由于廉价商用无线电硬件可用性的增加，对卫星地面系统的欺骗和重放攻击已变得比以往任何时候都更容易实现。这对传统系统而言尤为严重，其中许多系统不提供密码学安全性，且无法通过补丁支持新型安全措施。本文探索了卫星系统中的无线电发射器指纹识别技术。我们引入了SatIQ系统，提出了利用发射器硬件特性（表现为下行信号中的损伤）进行传输认证的新型技术。我们特别研究了高采样率指纹识别，使指纹难以在没有同等高采样率发射硬件的情况下伪造，从而提高攻击成本。我们还考察了该方法在高强度大气噪声和多径散射下的难度，并分析了潜在解决方案。我们以铱星卫星星座为研究对象，以25 MS/s的采样率收集了1,705,202条消息。利用这些数据，我们训练了一个由自编码器与孪生神经网络组成的指纹识别模型，使模型能够学习保留身份信息的消息头部高效编码。我们通过使用软件定义无线电重放消息来演示系统在攻击下的鲁棒性，实现了0.120的等错误率和0.946的ROC AUC值。最后，我们通过在训练数据与测试数据之间引入时间间隔分析了其时间稳定性，并通过引入未见过的全新发射器分析了其可扩展性。我们得出结论：我们的技术有助于构建时间稳定的系统，可在无需重新训练的情况下立即用于新发射器，并通过提高攻击所需成本来抵御欺骗和重放攻击。