Revisiting Monte Carlo Strength Evaluation

The Monte Carlo method, proposed by Dell’Amico and Filippone, estimates a password’s rank within a probabilistic model for password generation, i.e., it determines the password’s strength according to this model. We propose several ideas to improve the precision or speed of the estimation. Through experimental tests, we demonstrate that improved sampling can yield slightly better precision. Moreover, additional precomputation results in faster estimations with a modest increase in memory usage.