WISE: Waveform Independent Signal Embedding for Covert Communication

Wireless signals are vulnerable to various security threats, like eavesdropping and jamming, due to the inherent broadcast nature of the wireless channel. Encryption may ensure the confidentiality of the data but does not guarantee successful communication among legitimate users in the presence of strong adversaries, like wideband jammers. In this scenario, hiding a secret signal in presence of another mundane ongoing communication is one of the ways to minimize its chances of getting intercepted. Wireless Steganography is a process of embedding a secret signal inside another signal that acts as a cover to hide the signal of interest. In this paper, we propose to encode secret bits into covert signals that are statistically indistinguishable from a hardware noise generated by a low-cost transmitter. As the covert signal resembles hardware noise, it can be transmitted over any waveform, making it adaptable and portable to any communication link. Each generated complex signal sample is merged with a cover signal sample, yielding a 50% embedding rate. We create the encoding and decoding models by creating a pair of complex-valued neural networks (NNs), which is trained in presence of another NN model, critic. The critic model differentiates between true hardware noise and encoder-generated covert signal, thus providing essential feedback to the NN pair to improve the encoding technique. The decoder undergoes a transfer learning process to adapt to the residual channel effects in over-the-air experiments. In an indoor testbed, we successfully decoded the covert communication that mimics a range of hardware noises and is transmitted using different modulation orders of cover OFDM waveform. Our steganalysis indicates that the covert signal can be generated to mimic specific hardware, which remains indistinguishable in different statistical tests. Our method performs an order of magnitude better in statistical steganalysis compared to the state-of-the-art method in this field.