A novel method for designing S-box based on chaotic map and Teaching–Learning-Based Optimization

Farah, Tarek; Rhouma, Rhouma; Belghith, Safya

doi:10.1007/s11071-016-3295-y

Cited by 143 publications

(52 citation statements)

References 26 publications

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“…For our S-box, its obtained maximum SAC is 0.6094, the minimum is 0.3750, and its average value 0.5093 is close to the desired value 0.5. Moreover, compared with the algorithm proposed in [40], the average value of the dependence matrix of the generated S-box is closer to the idea value 0.5. Tables 3 and 4 describe the BIC related criterion results of our S-box.…”

Section: Nonlinearity Analysismentioning

confidence: 77%

“…To verify the generated S-box, we analyze its cryptographic criteria and compare it with many other S-boxes designed in [6][7][8][9][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. Moreover, our experimental environment is i3 CPU 540 3.07 GHz, memory 2.00 GHz Inter Core, Matlab2012b.…”

Section: Cryptographic Criteria Analyses Of Proposed S-boxmentioning

confidence: 99%

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Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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As the unique nonlinear component of block ciphers, Substitution box (S-box) directly affects the safety of a cryptographic system. It is important and difficult to design strong S-box that simultaneously meets multiple cryptographic criteria such as bijection, nonlinearity, strict avalanche criterion (SAC), bit independence criterion (BIC), differential probability (DP), and linear probability (LP). Though many chaotic S-boxes have been proposed, the cryptographic performance of most of them needs to be further improved. A new chaotic S-box based on the intertwining logistic map and bacterial foraging optimization is designed in this paper. It firstly iterates the intertwining logistic map to construct many S-boxes and then applies a bacterial foraging optimization algorithm to find the optimal S-box. Moreover, bacterial foraging optimization algorithm considers the nonlinearity and differential uniformity as the fitness functions in the optimization process. We experiment that the proposed S-box can effectively resist multiple types of cryptanalysis attacks.

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Section: Nonlinearity Analysismentioning

confidence: 77%

Section: Cryptographic Criteria Analyses Of Proposed S-boxmentioning

confidence: 99%

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Tian

2017

Mathematical Problems in Engineering

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“…Due to this condition, more than thousand S-Boxes can be generated by using chaotic map. In [33], the author introduced a method of teaching-learning for global solution. The global solution is believed to generate the best output permutation of S-Box.…”

Section: Chaotic Maps S-boxmentioning

confidence: 99%

Current implementation of advance encryption standard (AES) S-Box

Roslan¹,

Seman²,

Halim³

et al. 2018

J. Fundam and Appl Sci.

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Although the attack on cryptosystem is still not severe, the development of ongoing especially for the design of S-Box. Two main approach has been and algebraic method. Algebraic method as in current AES implementation the most secure S-Box design to date. This review paper will concentrate on two kinds of method of constructing AES S-Box, which are and heuristic approach. The objective is to review a method of constructing S or close to the original construction of AES S-Box especially for the heuristic approach. Finally, all the listed S-Boxes from these two methods will be compared in terms of their security performance which is nonlinearity and differential uniformity of th the potential approach to develop a new S-Box that is better than the block cipher; AES; S-box.

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“…A number of methods have been proposed to generate chaotic S‐boxes using chaotic trajectories of 1D and higher dimensional maps . Moreover, S‐boxes designed with a chaotic map can also be optimized using different optimization techniques to obtain highly nonlinear trajectories . A list of recently proposed S‐boxes with the design techniques used to generate these S‐boxes and their nonlinearity and differential approximation probability cryptographic properties is presented in Table .…”

Section: Introductionmentioning

confidence: 99%

Highly dispersive substitution box (S‐box) design using chaos

et al. 2020

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Highly dispersive S‐boxes are desirable in cryptosystems as nonlinear confusion sub‐layers for resisting modern attacks. For a near optimal cryptosystem resistant to modern cryptanalysis, a highly nonlinear and low differential probability (DP) value is required. We propose a method based on a piecewise linear chaotic map (PWLCM) with optimization conditions. Thus, the linear propagation of information in a cryptosystem appearing as a high DP during differential cryptanalysis of an S‐box is minimized. While mapping from the chaotic trajectory to integer domain, a randomness test is performed that justifies the nonlinear behavior of the highly dispersive and nonlinear chaotic S‐box. The proposed scheme is vetted using well‐established cryptographic performance criteria. The proposed S‐box meets the cryptographic performance criteria and further minimizes the differential propagation justified by the low DP value. The suitability of the proposed S‐box is also tested using an image encryption algorithm. Results show that the proposed S‐box as a confusion component entails a high level of security and improves resistance against all known attacks.

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A novel method for designing S-box based on chaotic map and Teaching–Learning-Based Optimization

Cited by 143 publications

References 26 publications

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Chaotic S‐Box: Intertwining Logistic Map and Bacterial Foraging Optimization

Current implementation of advance encryption standard (AES) S-Box

Highly dispersive substitution box (S‐box) design using chaos

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