672 research outputs found

    Multidimensional linear cryptanalysis

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    Linear cryptanalysis is an important tool for studying the security of symmetric ciphers. In 1993 Matsui proposed two algorithms, called Algorithm 1 and Algorithm 2, for recovering information about the secret key of a block cipher. The algorithms exploit a biased probabilistic relation between the input and output of the cipher. This relation is called the (one-dimensional) linear approximation of the cipher. Mathematically, the problem of key recovery is a binary hypothesis testing problem that can be solved with appropriate statistical tools. The same mathematical tools can be used for realising a distinguishing attack against a stream cipher. The distinguisher outputs whether the given sequence of keystream bits is derived from a cipher or a random source. Sometimes, it is even possible to recover a part of the initial state of the LFSR used in a key stream generator. Several authors considered using many one-dimensional linear approximations simultaneously in a key recovery attack and various solutions have been proposed. In this thesis a unified methodology for using multiple linear approximations in distinguishing and key recovery attacks is presented. This methodology, which we call multidimensional linear cryptanalysis, allows removing unnecessary and restrictive assumptions. We model the key recovery problems mathematically as hypothesis testing problems and show how to use standard statistical tools for solving them. We also show how the data complexity of linear cryptanalysis on stream ciphers and block ciphers can be reduced by using multiple approximations. We use well-known mathematical theory for comparing different statistical methods for solving the key recovery problems. We also test the theory in practice with reduced round Serpent. Based on our results, we give recommendations on how multidimensional linear cryptanalysis should be used

    Multidimensional Zero-Correlation Linear Cryptanalysis of the Block Cipher KASUMI

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    The block cipher KASUMI is widely used for security in many synchronous wireless standards. It was proposed by ETSI SAGE for usage in 3GPP (3rd Generation Partnership Project) ciphering algorthms in 2001. There are a great deal of cryptanalytic results on KASUMI, however, its security evaluation against the recent zero-correlation linear attacks is still lacking so far. In this paper, we select some special input masks to refine the general 5-round zero-correlation linear approximations combining with some observations on the FLFL functions and then propose the 6-round zero-correlation linear attack on KASUMI. Moreover, zero-correlation linear attacks on the last 7-round KASUMI are also introduced under some weak keys conditions. These weak keys take 2−142^{-14} of the whole key space. The new zero-correlation linear attack on the 6-round needs about 2852^{85} encryptions with 262.82^{62.8} known plaintexts. For the attack under weak keys conditions on the last 7 round, the data complexity is about 262.12^{62.1} known plaintexts and the time complexity 2110.52^{110.5} encryptions

    Multidimensional zero-correlation attacks on lightweight block cipher HIGHT: Improved cryptanalysis of an ISO standard

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    AbstractHIGHT is a block cipher designed in Korea with the involvement of Korea Information Security Agency. It was proposed at CHES 2006 for usage in lightweight applications such as sensor networks and RFID tags. Lately, it has been adopted as ISO standard. Though there is a great deal of cryptanalytic results on HIGHT, its security evaluation against the recent zero-correlation linear attacks is still lacking. At the same time, the Feistel-type structure of HIGHT suggests that it might be susceptible to this type of cryptanalysis. In this paper, we aim to bridge this gap.We identify zero-correlation linear approximations over 16 rounds of HIGHT. Based upon those, we attack 27-round HIGHT (round 4 to round 30) with improved time complexity and practical memory requirements. This attack of ours is the best result on HIGHT to date in the classical single-key setting. We also provide the first attack on 26-round HIGHT (round 4 to round 29) with the full whitening key

    Separable Statistics and Multidimensional Linear Cryptanalysis

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    Multidimensional linear cryptanalysis of block ciphers is improved in this work by introducing a number of new ideas. Firstly, formulae is given to compute approximate multidimensional distributions of the encryption algorithm internal bits. Conventional statistics like LLR (Logarithmic Likelihood Ratio) do not fit to work in Matsui’s Algorithm 2 for large dimension data, as the observation may depend on too many cipher key bits. So, secondly, a new statistic which reflects the structure of the cipher round is constructed instead. Thirdly, computing the statistic values that will fall into a critical region is presented as an optimisation problem for which an efficient algorithm is suggested. The algorithm works much faster than brute forcing all relevant key bits to compute the statistic. An attack for 16-round DES was implemented. We got an improvement over Matsui’s attack on DES in data and time complexity keeping success probability the same. With 241.81 plaintext blocks and success rate 0.83 (computed theoretically) we found 241.46 (which is close to the theoretically predicted number 241.81) key-candidates to 56-bit DES key. Search tree to compute the statistic values which fall into the critical region incorporated 245.45 nodes in the experiment and that is at least theoretically inferior in comparison with the final brute force. To get success probability 0.85, which is a fairer comparison to Matsui’s results, we would need 241.85 data and to brute force 241.85 key-candidates. That compares favourably with 243 achieved by Matsui

    Multidimensional Linear Cryptanalysis of Feistel Ciphers

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    This paper presents new generic attacks on Feistel ciphers that incorporate the key addition at the input of the non-invertible round function only. This feature leads to a specific vulnerability that can be exploited using multidimensional linear cryptanalysis. More specifically, our approach involves using key-independent linear trails so that the distribution of a combination of the plaintext and ciphertext can be computed. This makes it possible to use the likelihood-ratio test as opposed to the χ2 test. We provide theoretical estimates of the cost of our generic attacks and verify these experimentally by applying the attacks to CAST-128 and LOKI91. The theoretical and experimental findings demonstrate that the proposed attacks lead to significant reductions in data-complexity in several interesting cases

    Statistical Tests for Key Recovery Using Multidimensional Extension of Matsui\u27s Algorithm 1

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    In one dimension, there is essentially just one binomially distributed statistic, bias or correlation, for testing correctness of a key bit in Matsui\u27s Algorithm 1. In multiple dimensions, different statistical approaches for finding the correct key candidate are available. The purpose of this work is to investigate the efficiency of such test in theory and practice, and propose a new key class ranking statistic using distributions based on multidimensional linear approximation and generalisation of the ranking statistic presented by Selc cuk
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