This paper proposes to investigate the impact of the channel model for authentication systems based on codes that\nare corrupted by a physically unclonable noise such as the one emitted by a printing process. The core of such a\nsystem for the receiver is to perform a statistical test in order to recognize and accept an original code corrupted by\nnoise and reject any illegal copy or a counterfeit. This study highlights the fact that the probability of type I and type II\nerrors can be better approximated, by several orders of magnitude, when using the Cram�©r-Chernoff theorem instead\nof a Gaussian approximation. The practical computation of these error probabilities is also possible using Monte Carlo\nsimulations combined with the importance sampling method. By deriving the optimal test within a Neyman-Pearson\nsetup, a first theoretical analysis shows that a thresholding of the received code induces a loss of performance. A\nsecond analysis proposes to find the best parameters of the channels involved in the model in order to maximize the\nauthentication performance. This is possible not only when the opponentâ��s channel is identical to the legitimate\nchannel but also when the opponentâ��s channel is different, leading this time to a min-max game between the two\nplayers. Finally, we evaluate the impact of an uncertainty for the receiver on the opponent channel, and we show that\nthe authentication is still possible whenever the receiver can observe forged codes and uses them to estimate the\nparameters of the model.
Loading....