On the limiting mean values in probabilistic models of time-memory-data tradeoff methods

Time-memory-data tradeoff methods are used to solve one-way function inversion problems. This work provides some mathematical results aimed to the complexity analysis of the most known methods. We introduce a set of random variables depending on the generation sizes and on the total number of particles in a Galton–Watson process considered as a model of the main characteristics of these methods. The limit behavior of their mean values is studied. This work develops the results presented by the author at the CTCrypt 2013 workshop.