Probabilistic signature based generalized framework for differential fault analysis of stream ciphers

Abstract

Differential Fault Attack (DFA) considers injection of faults and the most general set-up should take care of faults at random location and random time. Then one should be able to identify the exact location as well as the exact timing of the fault (including the multi bit ones) with the help of fault signatures. In this paper we solve the problem of DFA under a general frame-work, introducing the idea of probabilistic signatures. The method considers the Maximum Likelihood approach related to probability distributions. Our techniques subsume all the existing DFAs against the Grain family, MICKEY 2.0 and Trivium. In the process we provide improved fault attacks for all the versions of Grain family and also for MICKEY 2.0. Our generalized method successfully takes care of the cases where certain parts of the keystream bits are missing (this situation may arise for authentication purpose). In particular, we show that the unsolved problem of identifying the faults in random time for Grain 128a can be solved in this manner. Moreover, for MICKEY 2.0, our method not only provides improvement in fault identification probability but also reduces the required faults by 60 %, compared to the best known result.