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Recent years have seen an increasing involvement of Deep Learning in the cryptanalysis of various ciphers. The present study is inspired by past works on differential distinguishers, to develop a Deep Neural Network-based differential…

Cryptography and Security · Computer Science 2021-12-10 Aayush Jain , Varun Kohli , Girish Mishra

In this paper we define a new (output) multiplicative differential, and the corresponding $c$-differential uniformity. With this new concept, even for characteristic $2$, there are perfect $c$-nonlinear (PcN) functions. We first…

Information Theory · Computer Science 2019-09-10 Pal Ellingsen , Patrick Felke , Constanza Riera , Pantelimon Stanica , Anton Tkachenko

In a prior paper \cite{EFRST20}, two of us, along with P. Ellingsen, P. Felke and A. Tkachenko, 1defined a new (output) multiplicative differential, and the corresponding $c$-differential uniformity, which has the potential of extending…

Information Theory · Computer Science 2021-03-23 Sihem Mesnager , Constanza Riera , Pantelimon Stanica , Haode Yan , Zhengchun Zhou

Differential cryptanalysis famously uses statistical biases in the propagation of differences in a block cipher to attack the cipher. In this paper, we investigate the existence of more general statistical biases in the differences. To this…

Cryptography and Security · Computer Science 2022-08-09 Daniele Bartoli , Lukas Kölsch , Giacomo Micheli

In a prior paper [14], along with P. Ellingsen, P. Felke and A. Tkachenko, we defined a new (output) multiplicative differential, and the corresponding c-differential uniformity, which has the potential of extending differential…

Cryptography and Security · Computer Science 2020-07-07 Constanza Riera , Pantelimon Stanica

In CRYPTO 2019, Gohr presented differential-neural cryptanalysis by building the differential distinguisher with a neural network, achieving practical 11-, and 12-round key recovery attack for Speck32/64. Inspired by this framework, we…

Cryptography and Security · Computer Science 2023-01-30 Liu Zhang , Jinyu Lu , Zilong Wang , Chao Li

In this paper we generalize Dillon's switching method to characterize the exact $c$-differential uniformity of functions constructed via this method. More precisely, we modify some PcN/APcN and other functions with known $c$-differential…

Information Theory · Computer Science 2022-04-20 Chunlei Li , Constanza Riera , Pantelimon Stanica

EFRST20, the notion of $c$-differentials was introduced as a potential expansion of differential cryptanalysis against block ciphers utilizing substitution boxes. Drawing inspiration from the technique of higher order differential…

Information Theory · Computer Science 2021-11-09 Aaron Geary , Marco Calderini , Constanza Riera , Pantelimon Stanica

In CRYPTO'19, Gohr proposed a new cryptanalysis strategy using machine learning algorithms. Combining the differential-neural distinguisher with a differential path and integrating the advanced key recovery procedure, Gohr achieved a…

Cryptography and Security · Computer Science 2022-04-14 Liu Zhang , Zilong Wang

Traditional cryptography is suffering a huge threat from the development of quantum computing. While many currently used public-key cryptosystems would be broken by Shor's algorithm, the effect of quantum computing on symmetric ones is…

Quantum Physics · Physics 2018-07-24 Huiqin Xie , Li Yang

Recently, a new concept called the $c$-differential uniformity was proposed by Ellingsen et al. (2020), which allows to simplify some types of differential cryptanalysis. Since then, finding functions having low $c$-differential uniformity…

Information Theory · Computer Science 2022-06-27 Jaeseong Jeong , Namhun Koo , Soonhak Kwon

Differential uniformity is a significant concept in cryptography as it quantifies the degree of security of S-boxes respect to differential attacks. Power functions of the form $F(x)=x^d$ with low differential uniformity have been…

Information Theory · Computer Science 2020-12-09 Nian Li , Yanan Wu , Xiangyong Zeng , Xiaohu Tang

Facing the worldwide steady progress in building quantum computers, it is crucial for cryptographic community to design quantum-safe cryptographic primitives. To achieve this, we need to investigate the capability of cryptographic analysis…

Quantum Physics · Physics 2024-07-23 Huiqin Xie , Li Yang

We defined in~\cite{EFRST20} a new multiplicative $c$-differential, and the corresponding $c$-differential uniformity and we characterized the known perfect nonlinear functions with respect to this new concept, as well as the inverse in any…

Information Theory · Computer Science 2020-04-27 Pantelimon Stanica

Permutations over $F_{2^{2k}}$ with low differential uniform, high algebraic degree and high nonlinearity are of great cryptographical importance since they can be chosen as the substitution boxes (S-boxes) for many block ciphers. A well…

Information Theory · Computer Science 2014-07-21 Jie Peng , Chik How Tan , Qichun Wang

The $c$-differential uniformity is recently proposed to reflect resistance against some variants of differential attack. Finding functions with low $c$-differential uniformity is attracting attention from many researchers. For even…

Information Theory · Computer Science 2022-02-07 Jaeseong Jeong , Namhun Koo , Soonhak Kwon

We investigate permutation polynomials F over finite fields F_{p^n} whose generalized derivative maps x -> F(x + a) - cF(x) are themselves permutations for all nonzero shifts a. This property, termed perfect c-nonlinearity (PcN), represents…

Information Theory · Computer Science 2026-02-26 Ranit Dutta , Pantelimon Stanica , Bimal Mandal

Due to the superiority of quantum computing, traditional cryptography is facing severe threat. This makes the security evaluation of cryptographic systems in quantum attack models significant and urgent. For symmetric ciphers, the security…

Quantum Physics · Physics 2024-07-16 Huiqin Xie , Qiqing Xia , Ke Wang , Yanjun Li , Li Yang

A wide range of numerical methods exists for computing polynomial approximations of solutions of ordinary differential equations based on Chebyshev series expansions or Chebyshev interpolation polynomials. We consider the application of…

Symbolic Computation · Computer Science 2014-07-11 Alexandre Benoit , Mioara Joldes , Marc Mezzarobba

In this article, we introduce new notions $cc$-differential uniformity, $cc$-differential spectrum, PccN functions and APccN functions, and investigate their properties. We also introduce $c$-CCZ equivalence, $c$-EA equivalence, and…

Information Theory · Computer Science 2023-01-24 Nhan-Phu Chung , Jaeseong Jeong , Namhun Koo , Soonhak Kwon
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