A new method for Searching Optimal Differential and Linear Trails in ARX Ciphers

In this paper, we propose an automatic tool to search for optimal differential and linear trails in ARX ciphers. It\u27s shown that a modulo addition can be divided into sequential small modulo additions with carry bit, which turns an ARX cipher into an S-box-like cipher. From this insight, we introduce the concepts of carry-bit-dependent difference distribution table (CDDT) and carry-bit-dependent linear approximation table (CLAT). Based on them, we give efficient methods to trace all possible output differences and linear masks of a big modulo addition, with returning their differential probabilities and linear correlations simultaneously. Then an adapted Matsui\u27s algorithm is introduced, which can find the optimal differential and linear trails in ARX ciphers. Besides, the superiority of our tool\u27s potency is also confirmed by experimental results for round-reduced versions of HIGHT and SPECK. More specifically, we find the optimal differential trails for up to 10 rounds of HIGHT, reported for the first time. We also find the optimal differential trails for 10, 12, 16, 8 and 8 rounds of SPECK32/48/64/96/128, and report the provably optimal differential trails for SPECK48 and SPECK64 for the first time. The optimal linear trails for up to 9 rounds of HIGHT are reported for the first time, and the optimal linear trails for 22, 13, 15, 9 and 9 rounds of SPECK32/48/64/96/128 are also found respectively. These results evaluate the security of HIGHT and SPECK against differential and linear cryptanalysis. Also, our tool is useful to estimate the security in the design of ARX ciphers

A Survey of ARX-based Symmetric-key Primitives

Addition Rotation XOR is suitable for fast implementation symmetric –key primitives, such as stream and block ciphers. This paper presents a review of several block and stream ciphers based on ARX construction followed by the discussion on the security analysis of symmetric key primitives where the best attack for every cipher was carried out. We benchmark the implementation on software and hardware according to the evaluation metrics. Therefore, this paper aims at providing a reference for a better selection of ARX design strategy

Automated Truncation of Differential Trails and Trail Clustering in ARX

We propose a tool for automated truncation of differential trails in ciphers using modular addition, bitwise rotation, and XOR (ARX). The tool takes as input a differential trail and produces as output a set of truncated differential trails. The set represents all possible truncations of the input trail according to certain predefined rules. A linear-time algorithm for the exact computation of the differential probability of a truncated trail that follows the truncation rules is proposed. We further describe a method to merge the set of truncated trails into a compact set of non-overlapping truncated trails with associated probability and we demonstrate the application of the tool on block cipher Speck64. We have also investigated the effect of clustering of differential trails around a fixed input trail. The best cluster that we have found for 15 rounds has probability 2^−55.03 (consisting of 389 unique output differences) which allows us to build a distinguisher using 128 times less data than the one based on just the single best trail, which has probability 2^−62. Moreover, we show examples for Speck64 where a cluster of trails around a suboptimal (in terms of probability) input trail results in higher overall probability compared to a cluster obtained around the best differential trail

A Bit-Vector Differential Model for the Modular Addition by a Constant

ARX algorithms are a class of symmetric-key algorithms constructed by Addition, Rotation, and XOR, which achieve the best software performances in low-end microcontrollers. To evaluate the resistance of an ARX cipher against differential cryptanalysis and its variants, the recent automated methods employ constraint satisfaction solvers, such as SMT solvers, to search for optimal characteristics. The main difficulty to formulate this search as a constraint satisfaction problem is obtaining the differential models of the non-linear operations, that is, the constraints describing the differential probability of each non-linear operation of the cipher. While an efficient bit-vector differential model was obtained for the modular addition with two variable inputs, no differential model for the modular addition by a constant has been proposed so far, preventing ARX ciphers including this operation from being evaluated with automated methods. In this paper, we present the first bit-vector differential model for the n-bit modular addition by a constant input. Our model contains O(log2(n)) basic bit-vector constraints and describes the binary logarithm of the differential probability. We also represent an SMT-based automated method to look for differential characteristics of ARX, including constant additions, and we provide an open-source tool ArxPy to find ARX differential characteristics in a fully automated way. To provide some examples, we have searched for related-key differential characteristics of TEA, XTEA, HIGHT, and LEA, obtaining better results than previous works. Our differential model and our automated tool allow cipher designers to select the best constant inputs for modular additions and cryptanalysts to evaluate the resistance of ARX ciphers against differential attacks.acceptedVersio

Automatic Search for the Best Trails in ARX: Application to Block Cipher Speck

We propose the first adaptation of Matsui's algorithm for finding the best differential and linear trails to the class of ARX ciphers. It is based on a branch-and-bound search strategy, does not use any heuristics and returns optimal results. The practical application of the new algorithm is demonstrated on reduced round variants of block ciphers from the Speck family. More specifically, we report the probabilities of the best differential trails for up to 10, 9, 8, 7, and 7 rounds of Speck32, Speck48, Speck64, Speck96 and Speck128 respectively, together with the exact number of differential trails that have the best probability. The new results are used to compute bounds, under the Markov assumption, on the security of Speck against single-trail differential cryptanalysis. Finally, we propose two new ARX primitives with provable bounds against single-trail differential and linear cryptanalysis -- a long standing open problem in the area of ARX design

STP Models of Optimal Differential and Linear Trail for S-box Based Ciphers

Automatic tools have played an important role in designing new cryptographic primitives and evaluating the security of ciphers. Simple Theorem Prover constraint solver (STP) has been used to search for differential/linear trails of ciphers. This paper proposes general STP-based models searching for differential and linear trails with the optimal probability and correlation for S-box based ciphers. In order to get trails with the best probability or correlation for ciphers with arbitrary S-box, we give an efficient algorithm to describe probability or correlation of S-Box. Based on the algorithm we present a search model for optimal differential and linear trails, which is efficient for ciphers with S-Boxes whose DDTs/LATs contain entities not equal to the power of two. Meanwhile, the STP-based model for single-key impossible differentials considering key schedule is proposed, which traces the propagation of values from plaintext to ciphertext instead of propagations of differences. And we found that there is no 5-round AES-128 single-key truncated impossible differential considering key schedule, where input and output differences have only one active byte respectively. Finally, our proposed models are utilized to search for trails of bit-wise ciphers GIFT-128, DES, DESL and ICEBERG and word-wise ciphers ARIA, SM4 and SKINNY-128. As a result, improved results are presented in terms of the number of rounds or probabilities/correlations

A MIQCP-Based Automatic Search Algorithm for Differential-Linear Trails of ARX Ciphers(Long Paper)

Differential-linear (DL) cryptanalysis has undergone remarkable advancements since it was first proposed by Langford and Hellman \cite{langford1994differential} in 1994. At CRYPTO 2022, Niu et al. studied the (rotational) DL cryptanalysis of $n$-bit modulo additions with 2 inputs, i.e., $\boxplus_2$, and presented a technique for evaluating the (rotational) DL correlation of ARX ciphers. However, the problem of how to automatically search for good DL trails on ARX with solvers was left open, which is the focus of this work. In this paper, we solve this open problem through some techniques to reduce complexity and a transformation technique from matrix multiplication chain to Mixed Integer Quadratically-Constrained Programs (MIQCP). First, the computational complexity of the DL correlation of $\boxplus_2$ is reduced to approximately one-eighth of the state of art, which can be computed by a $2\times2$ matrix multiplication chain of the same length as before. Some methods to further reduce complexity in special cases have been studied. Additionally, we present how to compute the extended (rotational) DL correlations of $\boxplus_k$ for $k\ge 2$, where two output linear masks of the cipher pairs can be different. Second, to ensure that the existing solver Gurobi\footnote{The solver used in this paper is Gurobi, and some ready-made functions in Gurobi are also used, such as LOG\_2 and ABS. The source code is available at \url{https://}. } can compute DL correlations of $\boxplus_2$, we propose a method to transform an arbitrary matrix multiplication chain into a MIQCP, which forms the foundation of our automatic search of DL trails in ARX ciphers. Third, in ARX ciphers, we use a single DL trail under some explicit conditions to give a good estimate of the correlation, which avoids the exhaustion of intermediate differences. We then derive an automatic method for evaluating the DL correlations of ARX, which we apply to Alzette and some versions of SPECK. Experimentally verified results confirm the validity of our method, with the predicted correlations being close to the experimental ones. To the best of our knowledge, this method finds the best DL distinguishers for these ARX primitives currently. Furthermore, we presented the lowest time-complexity attacks against 12-14 rounds of SPECK32 to date

Automatic Search of Bit-Based Division Property for ARX Ciphers and Word-Based Division Property

Division property is a generalized integral property proposed by Todo at Eurocrypt 2015. Previous tools for automatic searching are mainly based on the Mixed Integer Linear Programming (MILP) method and trace the division property propagation at the bit level. In this paper, we propose automatic tools to detect ARX ciphers\u27 division property at the bit level and some specific ciphers\u27 division property at the word level. For ARX ciphers, we construct the automatic searching tool relying on Boolean Satisfiability Problem (SAT) instead of MILP, since SAT method is more suitable in the search of ARX ciphers\u27 differential/linear characteristics. The propagation of division property is translated into a system of logical equations in Conjunctive Normal Form (CNF). Some logical equations can be dynamically adjusted according to different initial division properties and stopping rule, while the others corresponding to r-round propagations remain the same. Moreover, our approach can efficiently identify some optimized distinguishers with lower data complexity. As a result, we obtain a 17-round distinguisher for SHACAL-2, which gains four more rounds than previous work, and an 8-round distinguisher for LEA, which covers one more round than the former one. For word-based division property, we develop the automatic search based on Satisfiability Modulo Theories (SMT), which is a generalization of SAT. We model division property propagations of basic operations and S-boxes by logical formulas, and turn the searching problem into an SMT problem. With some available solvers, we achieve some new distinguishers. For CLEFIA, 10-round distinguishers are obtained, which cover one more round than the previous work. For the internal block cipher of Whirlpool, the data complexities of 4/5-round distinguishers are improved. For Rijndael-192 and Rijndael-256, 6-round distinguishers are presented, which attain two more rounds than the published ones. Besides, the integral attacks for CLEFIA are improved by one round with the newly obtained distinguishers

Automatic Differential Analysis of ARX Block Ciphers with Application to SPECK and LEA

In this paper, we focus on the automatic differential cryptanalysis of ARX block ciphers with respect to XOR-difference, and develop Mouha et al.\u27s framework for finding differential characteristics by adding a new method to construct long characteristics from short ones. The new method reduces the searching time a lot and makes it possible to search differential characteristics for ARX block ciphers with large word sizes such as $n=48,64$. What\u27s more, we take the differential effect into consideration and find that the differential probability increases by a factor of $1.4\sim 8$ for SPECK and about $2^{10}$ for LEA when multiple characteristics are counted in. The efficiency of our method is demonstrated by improved attacks of SPECK and LEA, which attack 1, 1, 4 and 6 more rounds of SPECK48, SPECK64, SPECK96 and SPECK128, respectively, and 2 more rounds of LEA than previous works

CLAASP: a Cryptographic Library for the Automated Analysis of Symmetric Primitives

This paper introduces CLAASP, a Cryptographic Library for the Automated Analysis of Symmetric Primitives. The library is designed to be modular, extendable, easy to use, generic, efficient and fully automated. It is an extensive toolbox gathering state-of-the-art techniques aimed at simplifying the manual tasks of symmetric primitive designers and analysts. CLAASP is built on top of Sagemath and is open-source under the GPLv3 license. The central input of CLAASP is the description of a cryptographic primitive as a list of connected components in the form of a directed acyclic graph. From this representation, the library can automatically: (1) generate the Python or C code of the primitive evaluation function, (2) execute a wide range of statistical and avalanche tests on the primitive, (3) generate SAT, SMT, CP and MILP models to search, for example, differential and linear trails, (4) measure algebraic properties of the primitive, (5) test neural-based distinguishers. In this work, we also present a comprehensive survey and comparison of other software libraries aiming at similar goals as CLAASP