MEHMET YILDIRIM

Binary Classifier Wire-Resistance Attack on KLJN: Bayes-Optimal Limit at a Narrow Resistor Gap

Machine learning is shown not to increase Eve’s successful bit-guessing probability in the binary-classifier-based wire-resistance attack on the Kirchhoff Law-Johnson Noise (KLJN) key exchange when the resistor gap is narrow. Using time-domain simulations of a non-ideal KLJN loop...