Protecting Legitimate SEI Security Approaches from Phase-Based Obfuscation Attacks

Specific Emitter Identification (SEI) has proven to be an effective means for passively identifying emitters using unique and distinct features that are unintentionally imparted to waveforms during their formation and transmission. Primarily, the assumption is that the to-be-identified emitters are passive devices incapable or unwilling to resist SEI. However, cost-effective software-defined radios and open-source deep learning algorithms are leading investigators to challenge this assumption. They show that previously exploited features can be modified to reduce or defeat SEI. Recently, RF-Veil has been proposed to combat such attacks by providing emitters with an active means to obfuscate their waveform features. The result is an eavesdropping and impersonation attack resilient SEI process. Despite RF-Veil's security and privacy focus, it is fair to assume that nefarious actors will attempt to abuse it to thwart legitimate SEI security processes. Therefore, this work investigates the identification of nefarious emitters that employ RF-Veil to thwart legitimate SEI security processes. The results show that there is an inherent Residual Phase Offset (RPO) present in preambles that are not removed in traditional phase offset correction. Removing RPO improves SEI performance when using the phase representation of IQ samples and significantly reduces RF-Veil's negative impact on SEI.