scholarly journals Construction Method and Performance Analysis of Chaotic S-Box Based on a Memorable Simulated Annealing Algorithm

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2115
Author(s):  
Juan Wang ◽  
Yangqing Zhu ◽  
Chao Zhou ◽  
Zhiming Qi
Keyword(s):  
Simulated Annealing ◽  
Block Cipher ◽  
Simulated Annealing Algorithm ◽  
Construction Method ◽  
Chaotic Mapping ◽  
Performance Indexes ◽  
Digital Chaos ◽  
The Matrix ◽  
Annealing Algorithm ◽  
And Performance

The substitution box (S-box) is the only nonlinear components in the symmetric block cipher. Its performance directly determines the security strength of the block cipher. With the dynamic characteristics degradation and the local periodic phenomenon of digital chaos, and the security problems caused by them becoming more and more prominent, how to efficiently generate an S-box with security guarantee based on chaos has gradually attracted the attention of cryptographers. In this paper, a chaotic S-box construction method is proposed based on a memorable simulated annealing algorithm (MSAA). The chaotic S-box set is produced by using the nonlinearity and randomness of the dynamic iteration of digital cascaded chaotic mapping. The composite objective function is constructed based on the analysis of the performance indexes of S-box. The MSAA is used to efficiently optimize the S-box set. The matrix segmentation and scrambling operations are carried out on the optimized S-box. The cryptographic performance of chaotic S-box is tested and analyzed, and compared with the mainstream chaotic S-box of the same kind. The results show that the S-box constructed in this paper can not only stably and efficiently generate chaotic S-box with better performance, but also make an effective exploration of the construction of chaotic S-boxes based on intelligent algorithms.

Fast Search of Lightweight Block Cipher Primitives via Swarm-like Metaheuristics for Cyber Security

2021 ◽  
Vol 21 (4) ◽  
pp. 1-15
Author(s):  
Xin Jin ◽  
Yuwei Duan ◽  
Ying Zhang ◽  
Yating Huang ◽  
Mengdong Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Block Cipher ◽  
Simulated Annealing Algorithm ◽  
Search Efficiency ◽  
Metaheuristic Algorithm ◽  
Search Results ◽  
Symmetric Key ◽  
Lightweight Block Cipher ◽  
Annealing Algorithm

With the construction and improvement of 5G infrastructure, more devices choose to access the Internet to achieve some functions. People are paying more attention to information security in the use of network devices. This makes lightweight block ciphers become a hotspot. A lightweight block cipher with superior performance can ensure the security of information while reducing the consumption of device resources. Traditional optimization tools, such as brute force or random search, are often used to solve the design of Symmetric-Key primitives. The metaheuristic algorithm was first used to solve the design of Symmetric-Key primitives of SKINNY. The genetic algorithm and the simulated annealing algorithm are used to increase the number of active S-boxes in SKINNY, thus improving the security of SKINNY. Based on this, to improve search efficiency and optimize search results, we design a novel metaheuristic algorithm, named particle swarm-like normal optimization algorithm (PSNO) to design the Symmetric-Key primitives of SKINNY. With our algorithm, one or better algorithm components can be obtained more quickly. The results in the experiments show that our search results are better than those of the genetic algorithm and the simulated annealing algorithm. The search efficiency is significantly improved. The algorithm we proposed can be generalized to the design of Symmetric-Key primitives of other lightweight block ciphers with clear evaluation indicators, where the corresponding indicators can be used as the objective functions.

scholarly journals Research on Optimal Control for the Vehicle Suspension Based on the Simulated Annealing Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Jie Meng ◽  
Qingzhang Chen ◽  
Ren He
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Target Function ◽  
Lqr Control ◽  
Performance Indexes ◽  
Lqr Controller ◽  
Chassis Control ◽  
Annealing Algorithm ◽  
And Control ◽  
Suspension Performance

A method is designed to optimize the weight matrix of the LQR controller by using the simulated annealing algorithm. This method utilizes the random searching characteristics of the algorithm to optimize the weight matrices with the target function of suspension performance indexes. This method improves the design efficiency and control performance of the LQR control, and solves the problem of the LQR controller when defining the weight matrices. And a simulation is provided for vehicle active chassis control. The result shows that the active suspension using LQR optimized by the genetic algorithm compared to the chassis controlled by the normal LQR and the passive one, shows better performance. Meanwhile, the problem of defining the weight matrices is greatly solved.

An Evolutionary Annealing Approach to Alloy Tensile Organization Evolution

2013 ◽  
Vol 710 ◽  
pp. 704-707
Author(s):  
Shu Zhang
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
High Temperature ◽  
Simulated Annealing Algorithm ◽  
Directional Migration ◽  
Migration Patterns ◽  
Matrix Channel ◽  
The Matrix ◽  
Method Optimization ◽  
Annealing Algorithm

Annealing evolutionary algorithm is a method optimization and hybrid the genetic algorithm and simulated annealing algorithm; it is the genetic algorithm has a strong grasp of the overall capacity, but also the algorithm using simulated annealing local search ability of stronger populations of genetic algorithm the probability of acceptance, to avoid the mature problem of genetic algorithm. Using γ'/γ ordered from a passage in the interface of the atom spread to another channel to analyze g raft form of fancies of ordered the width of the matrix channel with changes, thinks a photograph of the raft form at high temperatures of element diffusion occur. But the high temperature pull/pressure creep during different orientations of γ' phase happen, the rate of different raft form reason and in different orientations of single crystal alloy phase during the microstructure evolution ordered γ solute elements of the directional migration patterns are still unclear.

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