Provable Security Evaluation of Structures against Impossible Differential and Zero Correlation Linear Cryptanalysis

Impossible differential and zero correlation linear cryptanalysis are two of the most important cryptanalytic vectors. To characterize the impossible differentials and zero correlation linear hulls which are independent of the choices of the non-linear components, Sun et al. proposed the structure deduced by a block cipher at CRYPTO 2015. Based on that, we concentrate in this paper on the security of the SPN structure and Feistel structure with SP-type round functions. Firstly, we prove that for an SPN structure, if \alpha_1\rightarrow\beta_1 and \alpha_2\rightarrow\beta_ are possible differentials, \alpha_1|\alpha_2\rightarrow\beta_1|\beta_2 is also a possible differential, i.e., the OR | operation preserves differentials. Secondly, we show that for an SPN structure, there exists an r-round impossible differential if and only if there exists an r-round impossible differential \alpha\not\rightarrow\beta where the Hamming weights of both \alpha and \beta are 1. Thus for an SPN structure operating on m bytes, the computation complexity for deciding whether there exists an impossible differential can be reduced from O(2^{2m}) to O(m^2). Thirdly, we associate a primitive index with the linear layers of SPN structures. Based on the matrices theory over integer rings, we prove that the length of impossible differentials of an SPN structure is upper bounded by the primitive index of the linear layers. As a result we show that, unless the details of the S-boxes are considered, there do not exist 5-round impossible differentials for the AES and ARIA. Lastly, based on the links between impossible differential and zero correlation linear hull, we projected these results on impossible differentials to zero correlation linear hulls. It is interesting to note some of our results also apply to the Feistel structures with SP-type round functions

Searching for Subspace Trails and Truncated Differentials

Grassi et al. [Gra+16] introduced subspace trail cryptanalysis as a generalization of invariant subspaces and used it to give the first five round distinguisher for Aes. While it is a generic method, up to now it was only applied to the Aes and Prince. One problem for a broad adoption of the attack is a missing generic analysis algorithm. In this work we provide efficient and generic algorithms that allow to compute the provably best subspace trails for any substitution permutation cipher

Multivariate Profiling of Hulls for Linear Cryptanalysis

Extensions of linear cryptanalysis making use of multiple approximations, such as multiple and multidimensional linear cryptanalysis, are an important tool in symmetric-key cryptanalysis, among others being responsible for the best known attacks on ciphers such as Serpent and present. At CRYPTO 2015, Huang et al. provided a refined analysis of the key-dependent capacity leading to a refined key equivalence hypothesis, however at the cost of additional assumptions. Their analysis was extended by Blondeau and Nyberg to also cover an updated wrong key randomization hypothesis, using similar assumptions. However, a recent result by Nyberg shows the equivalence of linear dependence and statistical dependence of linear approximations, which essentially invalidates a crucial assumption on which all these multidimensional models are based. In this paper, we develop a model for linear cryptanalysis using multiple linearly independent approximations which takes key-dependence into account and complies with Nyberg’s result. Our model considers an arbitrary multivariate joint distribution of the correlations, and in particular avoids any assumptions regarding normality. The analysis of this distribution is then tailored to concrete ciphers in a practically feasible way by combining a signal/noise decomposition approach for the linear hulls with a profiling of the actual multivariate distribution of the signal correlations for a large number of keys, thereby entirely avoiding assumptions regarding the shape of this distribution. As an application of our model, we provide an attack on 26 rounds of present which is faster and requires less data than previous attacks, while using more realistic assumptions and far fewer approximations. We successfully extend the attack to present the first 27-round attack which takes key-dependence into account