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Abstract. Matsui's one-dimensional Alg. 2 can be used for recovering bits of the last round key of a block cipher. In this paper a truly multidimensional extension of Alg. 2 based on established statistical theory is presented. Two possible methods, an optimal method based on the log-likelihood ratio and a χ 2 -based goodness-of-fit test are compared in theory and by practical experiments on reduced round Serpent. The theory of advantage by Selçuk is generalised in multiple dimensions and the advantages and data, time and memory complexities for both methods are derived.

Abstract. PRESENT is a hardware-oriented block cipher suitable for resource constrained environment. In this paper we analyze PRESENT by the multidimensional linear cryptanalysis method. We claim that our attack can recover the 80-bit secret key of PRESENT up to 25 rounds out of 31 rounds with around 2 62.4 data complexity. Furthermore, we showed that the 26-round version of PRESENT can be attacked faster than key exhaustive search with the 2 64 data complexity by an advanced key search technique. Our results are superior to all the previous attacks. We demonstrate our result by performing the linear attacks on reduced variants of PRESENT. Our results exemplify that the performance of the multidimensional linear attack is superior compared to the classical linear attack.

Linear cryptanalysis introduced by Matsui is a statistical attack which exploits a binary linear relation between plaintext, ciphertext and key, either in Algorithm 1 for recovering one bit of information of the secret key of a block cipher, or in Algorithm 2 for ranking candidate values for a part of the key. The statistical model is based on the expected and observed bias of a single binary value. Multiple linear approximations have been used with the goal to make the linear attack more efficient. More bits of information of the key can potentially be recovered possibly using less data. But then also more elaborated statistical models are needed to capture the joint behaviour of several not necessarily independent binary variables. Also more options are available for generalising the statistics of a single variable to several variables. The multidimensional extension of linear cryptanalysis to be introduced in this paper considers using multiple linear approximations that form a linear subspace. Different extensions of Algorithm 1 and Algorithm 2 will be presented and studied. The methods will be based on known statistical tools such as goodness-of-fit test and log-likelihood ratio. The efficiency of the different methods will be measured and compared in theory and experiments using the concept of advantage introduced by Selçuk. The block cipher Serpent with a reduced number of rounds will be used as test bed. The multidimensional linear cryptanalysis will also be compared with previous methods that use biasedness of multiple linear approximations. It will be shown in the simulations that the multidimensional method is potentially more powerful. Its main theoretical advantage is that the statistical model can be given without the assumption about statistical independence of the linear approximations.

Abstract. In this paper, we present a new technique for Matsui's algorithm 2 using multidimensional linear approximation. We show that the data complexity of the attack can be reduced significantly by our method even when the linear hull effect is present. We apply our method to the key recovery attack on 5-round Serpent and demonstrate that our attack is superior to previous attacks. We present evidence that it is theoretically possible to reduce the data complexity of the linear attack against 10 round Serpent by factor of 2 20 when multiple approximations are used.