Recently, Gunn, Allison and Abbott (GAA) [http://arxiv.org/pdf/1402.2709v2.pdf] proposed a new scheme to utilize electromagnetic waves for eavesdropping on the Kirchhoff-law-Johnson-noise (KLJN) secure key distribution. We proved in a former paper [Fluct. Noise Lett. 13 (2014) 1450016] that GAA’s mathematical model is unphysical. Here we analyze GAA’s cracking scheme and show that, in the case of a loss-free cable, it provides less eavesdropping information than in the earlier (Bergou)-Scheuer-Yariv mean-square-based attack [Kish LB, Scheuer J, Phys. Lett. A 374:2140-2142 (2010)], while it offers no information in the case of a lossy cable. We also investigate GAA’s claim to be experimentally capable of distinguishing—using statistics over a few correlation times only—the distributions of two Gaussian noises with a relative variance difference of less than 10-8. Normally such distinctions would require hundreds of millions of correlations times to be observable. We identify several potential experimental artifacts as results of poor KLJN design, which can lead to GAA’s assertions: deterministic currents due to spurious harmonic components caused by ground loops, DC offset, aliasing, non-Gaussian features including non-linearities and other non-idealities in generators, and the timederivative nature of GAA’s scheme which tends to enhance all of these artifacts.

The Kirchhoff-law-Johnson-noise (KLJN) scheme is a statistical/physical secure key exchange system based on the laws of classical statistical physics to provide unconditional security. We used the LTSPICE industrial cable and circuit simulator to emulate one of the major active (invasive) attacks, the current injection attack, against the ideal and a practical KLJN system, respectively. We show that two security enhancement techniques, namely, the instantaneous voltage/current comparison method, and a simple privacy amplification scheme, independently and effectively eliminate the information leak and successfully preserve the system’s unconditional security.