New automatic tool for finding impossible differentials and zero-correlation linear approximations

2020 ◽  
Vol 64 (2) ◽  
Author(s):  
Tingting Cui ◽  
Shiyao Chen ◽  
Kai Fu ◽  
Meiqin Wang ◽  
Keting Jia
Keyword(s):  
Linear Approximations ◽  
Zero Correlation ◽  
Automatic Tool ◽  
Impossible Differentials

scholarly journals Analysis of AES, SKINNY, and Others with Constraint Programming

2017 ◽  
pp. 281-306 ◽  
Author(s):  
Siwei Sun ◽  
David Gerault ◽  
Pascal Lafourcade ◽  
Qianqian Yang ◽  
Yosuke Todo ◽  
...  
Keyword(s):  
Lower Bound ◽  
Constraint Programming ◽  
Open Problem ◽  
Simple Application ◽  
Programming Technique ◽  
Constraint Solver ◽  
Zero Correlation ◽  
Different Types ◽  
Symmetric Key ◽  
Impossible Differentials

Search for different types of distinguishers are common tasks in symmetrickey cryptanalysis. In this work, we employ the constraint programming (CP) technique to tackle such problems. First, we show that a simple application of the CP approach proposed by Gerault et al. leads to the solution of the open problem of determining the exact lower bound of the number of active S-boxes for 6-round AES-128 in the related-key model. Subsequently, we show that the same approach can be applied in searching for integral distinguishers, impossible differentials, zero-correlation linear approximations, in both the single-key and related-(twea)key model. We implement the method using the open source constraint solver Choco and apply it to the block ciphers PRESENT, SKINNY, and HIGHT (ARX construction). As a result, we find 16 related-tweakey impossible differentials for 12-round SKINNY-64-128 based on which we construct an 18-round attack on SKINNY-64-128 (one target version for the crypto competition https://sites.google.com/site/skinnycipher announced at ASK 2016). Moreover, we show that in some cases, when equipped with proper strategies (ordering heuristic, restart and dynamic branching strategy), the CP approach can be very efficient. Therefore, we suggest that the constraint programming technique should become a convenient tool at hand of the symmetric-key cryptanalysts.

scholarly journals A New Automatic Tool Searching for Impossible Differential of NIST Candidate ACE

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1576
Author(s):  
Jingyi Liu ◽  
Guoqiang Liu ◽  
Longjiang Qu
Keyword(s):  
Characteristic Matrix ◽  
Differential Attack ◽  
Optimal Permutation ◽  
The Usa ◽  
Standardization Process ◽  
Impossible Differential ◽  
Automatic Tool ◽  
Ace Algorithm ◽  
Impossible Differentials ◽  
Impossible Differential Cryptanalysis

The ACE algorithm is a candidate of the Lightweight Cryptography standardization process started by the National Institute of Standards and Technology (NIST) of the USA that passed the first round and successfully entered the second round. It is designed to achieve a balance between hardware cost and software efficiency for both authenticated encryption with associated data (AEAD) and hashing functionalities. This paper focuses on the impossible differential attack against the ACE permutation, which is the core component of the ACE algorithm. Based on the method of characteristic matrix, we build an automatic searching algorithm that can be used to search for structural impossible differentials and give the optimal permutation for ACE permutation and other SPN ciphers. We prove that there is no impossible differential of ACE permutation longer than 9 steps and construct two 8-step impossible differentials. In the end, we give the optimal word permutation against impossible differential cryptanalysis, which is π′=(2,4,1,0,3), and a safer word XOR structure of ACE permutation.

scholarly journals Improved Impossible Differentials and Zero-Correlation Linear Hulls of New Structure III

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jun He ◽  
Xuan Shen ◽  
Guoqiang Liu
Keyword(s):  
Block Cipher ◽  
Characteristic Matrix ◽  
Linear Cryptanalysis ◽  
The Core ◽  
Round Function ◽  
Linear Layer ◽  
Zero Correlation ◽  
Impossible Differential ◽  
Impossible Differentials ◽  
Impossible Differential Cryptanalysis

Impossible differential cryptanalysis and zero-correlation linear cryptanalysis are two kinds of most effective tools for evaluating the security of block ciphers. In those attacks, the core step is to construct a distinguisher as long as possible. In this paper, we focus on the security of New Structure III, which is a kind of block cipher structure with excellent resistance against differential and linear attacks. While the best previous result can only exploit one-round linear layer P to construct impossible differential and zero-correlation linear distinguishers, we try to exploit more rounds to find longer distinguishers. Combining the Miss-in-the-Middle strategy and the characteristic matrix method proposed at EUROCRYPT 2016, we could construct 23-round impossible differentials and zero-correlation linear hulls when the linear layer P satisfies some restricted conditions. To our knowledge, both of them are 1 round longer than the best previous works concerning the two cryptanalytical methods. Furthermore, to show the effectiveness of our distinguishers, the linear layer of the round function is specified to the permutation matrix of block cipher SKINNY which was proposed at CRYPTO 2016. Our results indicate that New Structure III has weaker resistance against impossible differential and zero-correlation linear attacks, though it possesses good differential and linear properties.

Squeak and rattle noise classification using radial basis function neural networks

2020 ◽  
Vol 68 (4) ◽  
pp. 283-293
Author(s):  
Oleksandr Pogorilyi ◽  
Mohammad Fard ◽  
John Davy ◽  
Mechanical and Automotive Engineering, School ◽  
Mechanical and Automotive Engineering, School ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
High Accuracy ◽  
Training Method ◽  
Vehicle Interior ◽  
Trained Classifier ◽  
Different Types ◽  
Noise Classification ◽  
Automatic Tool ◽  
Multi Class Classification

In this article, an artificial neural network is proposed to classify short audio sequences of squeak and rattle (S&R) noises. The aim of the classification is to see how accurately the trained classifier can recognize different types of S&R sounds. Having a high accuracy model that can recognize audible S&R noises could help to build an automatic tool able to identify unpleasant vehicle interior sounds in a matter of seconds from a short audio recording of the sounds. In this article, the training method of the classifier is proposed, and the results show that the trained model can identify various classes of S&R noises: simple (binary clas- sification) and complex ones (multi class classification).

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