用离散潜空间模型增强无线信号抗干扰能力
A look at adversarial attacks on radio waveforms from discrete latent space
- 将数字调制信号映射到离散潜空间，实现完美重建
- 对抗攻击下，解码后分类准确率显著下降但被潜空间抑制
- 潜空间分布变化可作为攻击检测线索，适合安全通信研究
我们设计了一种基于VQVAE的模型，将数字无线电信号映射至离散潜空间，并实现原始数据的完全可分类重构。针对高信噪比（SNR）下的射频数据点，我们分析了该模型在对抗攻击下的抑制能力。攻击聚焦于部分数字调制波形的幅度调制，通过同时扰动同相（I）和正交（Q）分量但保持其相位关系来生成对抗样本。对比未保持相位的同类强度攻击，我们测试了这些对抗样本在原始数据训练下达到100%准确率的分类器上的表现。结果表明，经由VQVAE重构后的对抗数据点，其分类准确率显著降低，证明了该模型能有效削弱攻击强度。我们还比较了攻击前后数据、重构数据与原始数据在I/Q平面中的分布。进一步通过多种方法和指标，对比有无攻击时的VQVAE潜空间概率分布。随着攻击强度变化，观察到离散潜空间中出现有趣性质，可能用于攻击检测。
原文摘要 · Abstract (English)
Having designed a VQVAE that maps digital radio waveforms into discrete latent space, and yields a perfectly classifiable reconstruction of the original data, we here analyze the attack suppressing properties of VQVAE when an adversarial attack is performed on high-SNR radio-frequency (RF) data-points. To target amplitude modulations from a subset of digitally modulated waveform classes, we first create adversarial attacks that preserve the phase between the in-phase and quadrature component whose values are adversarially changed. We compare them with adversarial attacks of the same intensity where phase is not preserved. We test the classification accuracy of such adversarial examples on a classifier trained to deliver 100% accuracy on the original data. To assess the ability of VQVAE to suppress the strength of the attack, we evaluate the classifier accuracy on the reconstructions by VQVAE of the adversarial datapoints and show that VQVAE substantially decreases the effectiveness of the attack. We also compare the I/Q plane diagram of the attacked data, their reconstructions and the original data. Finally, using multiple methods and metrics, we compare the probability distribution of the VQVAE latent space with and without attack. Varying the attack strength, we observe interesting properties of the discrete space, which may help detect the attacks.
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