2019
DOI: 10.1109/access.2019.2936447
|View full text |Cite
|
Sign up to set email alerts
|

A New Chaotic S-Box Generation Method Using Parameter Optimization of One Dimensional Chaotic Maps

Abstract: Chaotic systems have been used to generate the substitutional box structures. The existence of endless possibilities for the selection of the initial conditions and control parameters of the chaotic system has made it a necessity to use the optimization algorithms for generation of chaos based substitutional box structures. Most appropriate initial conditions and control parameters have been determined for four different discrete time chaotic systems using seven different optimization algorithms. A new substit… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
47
0
1

Year Published

2020
2020
2024
2024

Publication Types

Select...
8
2

Relationship

0
10

Authors

Journals

citations
Cited by 77 publications
(48 citation statements)
references
References 84 publications
0
47
0
1
Order By: Relevance
“…D. Lambić [5] proposed a novel method of S-Box design based on discrete chaotic maps. Tanyildizi and Erkan [6] proposed a chaotic S-Box generation method using parameter optimization of one dimensional chaotic maps. Çavuşoğlu et al [4] proposed a strong s-box generation algorithm based on a chaotic scaled zhongtang system.…”
Section: Introductionmentioning
confidence: 99%
“…D. Lambić [5] proposed a novel method of S-Box design based on discrete chaotic maps. Tanyildizi and Erkan [6] proposed a chaotic S-Box generation method using parameter optimization of one dimensional chaotic maps. Çavuşoğlu et al [4] proposed a strong s-box generation algorithm based on a chaotic scaled zhongtang system.…”
Section: Introductionmentioning
confidence: 99%
“…For example, the input 11110101, equal to f5, is transformed by S c to 5d. The characteristics of S c are summarized in Tables 3 and 4. 1 hill climbing without neighborhood search In [27], Table 5, a summary on the CF-based S-box constructions found in the literature is presented (an updated version of it is to be found in Table 6). We significantly outperform all of them in terms of ACNV and SAC, reaching the optimal SAC value of 0.5.…”
Section: Results Part Imentioning
confidence: 99%
“…Thus, the proposed S-box holds excellent nonlinearity performance compared to all competitor S-boxes. It is worth mention the proposed method holds the significant merit over the existing S-box methods previously investigated in [40,42,62,68,70,[78][79][80][81][82][83][84] in terms of nonlinearity performance as minimum NL of 112, maximum NL of 116 and average NL of 114 is achieved with the proposed method. -The SAC score of 0.4978 is quite close to ideal value of 0.5 and have an offset of only 0.0022 which is negligible.…”
Section: F Comparison Analysismentioning
confidence: 91%