scholarly journals AN EFFICIENT CHAOS-BASED OPTIMIZATION ALGORITHM APPROACH FOR CRYPTOGRAPHY

2012 ◽  
pp. 75-79
Author(s):  
RASHI VOHRA ◽  
BRAJESH PATEL
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Negative Impact ◽  
Chaotic Map ◽  
Pseudorandom Sequence ◽  
Secure Communications ◽  
Security Threats ◽  
Suggested Approach ◽  
Novel Approach ◽  
Algorithm Operation

The utmost negative impact of advancement of technology is an exponential increase in security threats, due to which tremendous demand for effective electronic security is increasing importantly. The principles of any security mechanism are confidentiality, authentication, integrity, non-repudiation, access control and availability. Cryptography is an essential aspect for secure communications. Many chaotic cryptosystem has been developed, as a result of the interesting relationship between the two field chaos and cryptography phenomenological behavior. In this paper, an overview of cryptography, optimization algorithm and chaos theory is provided and a novel approach for encryption and decryption based on chaos and optimization algorithms is discussed. In this article, the basic idea is to encrypt and decrypt the information using the concept of genetic algorithm with the pseudorandom sequence further used as a key in genetic algorithm operation for encryption: which is generated by application of chaotic map. This attempt result in good desirable cryptographic properties as a change in key will produce undesired result in receiver side. The suggested approach complements standard, algorithmic procedures, providing security solutions with novel features.

scholarly journals The Dynamic Analysis of a Novel Reconfigurable Cubic Chaotic Map and Its Application in Finite Field

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1420
Author(s):  
Chuanfu Wang ◽  
Yi Di ◽  
Jianyu Tang ◽  
Jing Shuai ◽  
Yuchen Zhang ◽  
...  
Keyword(s):  
Secure Communication ◽  
Chaotic Map ◽  
Digital Circuit ◽  
Pseudorandom Sequence ◽  
Periodic Behavior ◽  
Output Sequence ◽  
Digital Devices ◽  
Theoretical And Numerical Analysis ◽  
Dynamic Degradation ◽  
Sequence Generator

Dynamic degradation occurs when chaotic systems are implemented on digital devices, which seriously threatens the security of chaos-based pseudorandom sequence generators. The chaotic degradation shows complex periodic behavior, which is often ignored by designers and seldom analyzed in theory. Not knowing the exact period of the output sequence is the key problem that affects the application of chaos-based pseudorandom sequence generators. In this paper, two cubic chaotic maps are combined, which have symmetry and reconfigurable form in the digital circuit. The dynamic behavior of the cubic chaotic map and the corresponding digital cubic chaotic map are analyzed respectively, and the reasons for the complex period and weak randomness of output sequences are studied. On this basis, the digital cubic chaotic map is optimized, and the complex periodic behavior is improved. In addition, a reconfigurable pseudorandom sequence generator based on the digital cubic chaotic map is constructed from the point of saving consumption of logical resources. Through theoretical and numerical analysis, the pseudorandom sequence generator solves the complex period and weak randomness of the cubic chaotic map after digitization and makes the output sequence have better performance and less resource consumption, which lays the foundation for applying it to the field of secure communication.

scholarly journals A Novel Approach to Oil Layer Recognition Model Using Whale Optimization Algorithm and Semi-Supervised SVM

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 757
Author(s):  
Yongke Pan ◽  
Kewen Xia ◽  
Li Wang ◽  
Ziping He
Keyword(s):  
Optimization Algorithm ◽  
Oil And Gas ◽  
The Other ◽  
Whale Optimization Algorithm ◽  
Classification Model ◽  
Support Vector ◽  
Recognition Model ◽  
Novel Approach ◽  
Whale Optimization ◽  
Oil And Gas Reservoir

The dataset distribution of actual logging is asymmetric, as most logging data are unlabeled. With the traditional classification model, it is hard to predict the oil and gas reservoir accurately. Therefore, a novel approach to the oil layer recognition model using the improved whale swarm algorithm (WOA) and semi-supervised support vector machine (S3VM) is proposed in this paper. At first, in order to overcome the shortcomings of the Whale Optimization Algorithm applied in the parameter-optimization of the S3VM model, such as falling into a local optimization and low convergence precision, an improved WOA was proposed according to the adaptive cloud strategy and the catfish effect. Then, the improved WOA was used to optimize the kernel parameters of S3VM for oil layer recognition. In this paper, the improved WOA is used to test 15 benchmark functions of CEC2005 compared with five other algorithms. The IWOA–S3VM model is used to classify the five kinds of UCI datasets compared with the other two algorithms. Finally, the IWOA–S3VM model is used for oil layer recognition. The result shows that (1) the improved WOA has better convergence speed and optimization ability than the other five algorithms, and (2) the IWOA–S3VM model has better recognition precision when the dataset contains a labeled and unlabeled dataset in oil layer recognition.

scholarly journals Multi-user Remote Lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm

2021 ◽  
Vol 2 (2) ◽  
pp. 1-13
Author(s):  
Seid Miad Zandavi ◽  
Vera Chung ◽  
Ali Anaissi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Simplex Algorithm ◽  
Local Optimum ◽  
Hybrid Optimization Algorithm ◽  
Multimodal Function ◽  
Remote Laboratories ◽  
Remote Lab ◽  
Timetable Problem

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. The hybrid optimization algorithm, hybridization of the Nelder-Mead Simplex algorithm, and Non-dominated Sorting Genetic Algorithm (NSGA), named Simplex Non-dominated Sorting Genetic Algorithm (SNSGA), is proposed to optimize the timetable problem for the remote laboratories to coordinate shared access. The proposed algorithm utilizes the Simplex algorithm in terms of exploration and NSGA for sorting local optimum points with consideration of potential areas. SNSGA is applied to difficult nonlinear continuous multimodal functions, and its performance is compared with hybrid Simplex Particle Swarm Optimization, Simplex Genetic Algorithm, and other heuristic algorithms. The results show that SNSGA has a competitive performance to address timetable problems.

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