Combination Of Chaotic Maps Research Articles

Hybrid CHGSO Approach-Based EV Energy Regulation by Considering Incentive-Based Prosumer and Uncertainty

This paper proposes the hybrid approach for increasing the profit of prosumers and reducing the energy cost of the residents. The hybrid method is the combination of chaotic maps and the Henry gas solubility optimization algorithm (HGSO), hence it is called chaotic Henry gas solubility optimization (CHGSO). The proposed approach is the community-based microgrid that incorporates energy storage systems (ESS), electric vehicles (EVs) and photovoltaics (PV). Both ESS and EV are conserved as alternative sources of energy. The stored EV energy is used as a power source for homes and the grid by utilizing the Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) modes. The power flow of EV/ESS is controlled depending on the rate of charging and discharging. Here, the battery degradation cost is considered. The proposed approach solves the optimization problems, like battery degradation of EV/ESS, regulation of charge/discharge and provides optimal economic benefits. The proposed approach increases the prosumer profit through encouraging EV energy transactions through incentive-based pricing. Finally, the CHGSO method is performed in MATLAB and is compared with existing methods. From the simulation analysis, it can be concluded that the cost of CHGSO method is less and the prosumer participation has increased.

Colour image encryption based on hybrid bit-level scrambling, ciphering, and public key cryptography

This paper proposes an image encryption technique using three stages algorithms based on hyper-chaotic maps. In the first scenario, bit-level scrambling (BLS) using a 2D coupled chaotic map (2D-CCM) is used to encrypt the bits of the basic colour image. In the second strategy, the scrambled bit level is XORed with pseudo random bit generator (PRBG). The PRBG is designed using a combination of chaotic maps, including, logistic map (LM), sine map (SM), 5D chaotic map (5D-CM), enhanced quadratic map (EQM), and 2D henon SM (2D-HSM). The pubic key based on the Chebyshev polynomial chaotic map is used as the final phase of the encryption algorithms. The performance analysis of the proposed image encryption technique is validated through various criteria such as fundamental space analysis, correlation coefficient, entropy, the number of pixels changes rate (NPCR), and unified average-changing intensity (UACI). Also, the obtained results are compared with other recent studies. The simulation results demonstrated that the proposed technique has robust security and it provides the image with high protection against various attacks.

A Chaos‐Based Image Encryption Scheme Is Proposed Using Multiple Chaotic Maps

Everybody wants to maintain solitariness to some extent or entirely in his dealings with other people during different modes of communication. To retain privacy, researchers materialized distinct image encryption algorithms using chaotic maps. Due to their extraordinary features, most researchers employed multidimensional chaotic maps to barricade clandestine information or digital images from potential invaders. Still, multidimensional chaotic maps have many impediments conferred in the literature review. In this paper, we developed a cryptosystem utilizing multiple chaotic maps to mitigate the shortcoming of multidimensional chaotic maps. A distinctive approach is adopted to sire a key stream using a combination of chaotic maps and create a sequence of random integers linked with the pixels of the plain image to shatter the association between neighboring pixels of a plain image. Finally, diffusion is accomplished using the previously diffused pixels at a decimal level. Security and statistical analysis demonstrate that the presented encryption algorithm is robust against well‐known attacks. An ample key space indicates that it is best suited for secure communication.

An image encryption algorithm using the combination of chaotic maps

Nowadays, as the science and technology are advanced, users are more willing to use the visual data and also such kind of data in medical and military applications. Therefore, unauthorized access to personal and confidential information has become a critical problem in today’s digital world. Encryption is an appropriate method for fixing such problems. Due to high size of data and high correlation among the image’s adjacent pixels, texts encryption algorithms are not good for image encryption. In designing an algorithm for the future generations, three principles should be met: firstly, algorithm should be so simple that it is evaluated and analyzed easily, accurately and completely. Secondly, an encryption algorithm should have a security margin much more than the required for current identified attacks. Thirdly, in design, the tools and ideas already known and reliable should be utilized as much as possible. Hence, in this paper, an image encryption algorithm is proposed by combination of two Henon chaos and Logistic systems. Experimental results confirm and demonstrate that the proposed method yields better outcomes in the field of security against the statistical and differential attacks compared to the original AES encryption algorithm and previous modified encryption algorithms.

Security Analyses of Random Number Generation with Image Encryption Using Improved Chaotic Map

A chaotic system can have a series of values for the developing variable that completely repeat themselves, giving periodic behavior beginning from any point in that series. It is very sensitive to initial conditions and control parameters which make them suitable for image encryption. The two maps Duffing and Logistic maps are combined to generate a random sequence. The Logistic map is 1 Dimensional and contains one control parameter (r). Duffing map contains 2 dimensions X and Y, and two control parameters A and B. Both are XOR'ed to get the random numbers. The control parameters of Duffing map are controlled by the control parameter r. X and Y are looped to get repetitive iterations. The random sequences are analyzed for statistical tests for randomness, keyspace, key sensitivity (or) cross-correlation, periodicity, auto-correlation, information entropy, equilibrium, linear complexity, and speed are the analyses to verify their conformity for use in cryptographic applications. Image encryption is the process of encoding a grayscale image with the help of a series of random numbers created by using a combination of chaotic maps, in such a way that uncertified users can't access it. NPCR, UACI, Histogram, and Information Entropy are the analyses performed. Image encryption and secret key generation are presented based on the Duffing map and logistic chaotic map. The series of random numbers and the greyscale image pixels are XOR'ed to shuffle the pixels and it turned the original image into a cipher image.

Hybrid chaotic approaches to solve profit based unit commitment with plug-in electric vehicle and renewable energy sources in winter and summer

Recently power sectors have faced lots of challenges for huge penetration growths for renewable energy sources (RES) and effects of charging as well as discharging nature of plug-in electric vehicles (PEVs) to fulfill time varying power demands. The alteration of transport system as well as low carbon energy require not only for the efficiency measurements with large scale acceptance of the clean technology, but also the strategies for new energy managing to incorporate those innovations efficiently in present infrastructure. Thus development of PEVs are needed. Due to development of RES the fossils fuel consumption with greenhouse gas emission can be reduced. In the proposed research, authors have effectively given the combination of chaotic maps with Harris Hawks Optimizer, Sine Cosine Algorithm and Slime Mould Algorithm advancement strategy and assessed execution of the proposed improved technique for standard benchmark of PBUCP with considering effect of PEVs and RES in summer and winter are checked for small type to large type test systems i.e. 10-, 40- and 100-generating unit system are considered and profit of each are evaluated as outcome of this research.

Metaheuristics approaches to profit based unit commitment for GENCOs

The optimum scheduling with maximize the profit from those generating systems have to maintain lots of constraints which are uncertain by nature. There are also have stimulating responsibility of delivered power among the power units which are committed which matters to visit restrictions over a planned scheduled time period to accomplish minimal cost and maximum profit of power generations. In the proposed work, authors have effectively given the combination of chaotic maps with Harris Hawks Optimization with Sine Cosine Algorithm and Slime Mould Algorithm advancement strategy and assessed execution of the proposed improved technique, named as hCHHO-SCA and hCSMA-SCA for standard benchmark of PBUCP are checked for small to large scale test systems i.e. 10-, 40- and 100-generating unit systems are considered and profit of each are evaluated as outcomes are compared with the exiting optimization algorithms in this research work.

An improved brainstorm optimization using chaotic opposite-based learning with disruption operator for global optimization and feature selection

Optimization has increased its use in different domains for accurately solving challenging problems. Complex optimization problems require the use of methods that possess the capabilities to properly explore the search spaces. The traditional algorithms commonly tend to fail in suboptimal values during the optimization process; this fact affects the quality of the solutions. This situation occurs for different reasons, but the lack of diversity due to the use of exploitation operators is the most common. Brainstorm optimization is an alternative method based on the social strategy to generate new innovative ideas in work groups. In brainstorm optimization, each solution representing an idea and brainstorm process is performed using clustering algorithms. However, brainstorm optimization is not able to thoroughly explore the search space, and its diversity is reduced. It does not possess any mechanism to escape from suboptimal solutions. Besides, the computational effort is also increased in the iterative process. This paper presents a modified version of brainstorm optimization that improves its performance. In the proposed algorithm, chaotic maps and opposition-based learning are applied to initialize the solutions for a given problem. Moreover, in the optimization process, the positions of the initial population are updated using the disruptor operator. After updating the population, opposition-based learning is used again to analyze the opposite solutions. The combination of chaotic maps, opposition-based learning and disruption operator improve the exploration ability of brainstorm optimization by increasing the diversity of the population. The proposed method has been evaluated using a set of benchmark functions, and it has been also used for feature selection in data mining. The results show the high efficacy of the proposed method to determine the optimal solutions of the tested functions.

A class of higher-dimensional hyperchaotic maps

Based on the hybrid modulation coupling (HMC) pattern, a class of higher-dimensional (HD) hyperchaotic maps is proposed using three one-dimensional (1D) seed maps. The seed maps are chaotic maps or the combination of chaotic maps and non-chaotic maps. Taking the HMC of iterative chaotic map with infinite collapse (ICMIC), Sine map and a linear map (ISL-HMC) as an example, the equilibrium points are mathematically analyzed. The dynamical performance of the 3D ISL-HMC map is evaluated by phase diagram, Lyapunov exponents (LEs), bifurcation diagram and chaos diagram. Furthermore, compared with existing chaotic maps, complexity and distribution characteristic are analyzed. As application of the ISL-HMC map, a pseudorandom number generator (PRNG) is designed and tested by NIST SP 800-22 and TestU01. Experimental results show that the ISL-HMC map has rich dynamical behaviors and good randomness. So this class of HD hyperchaotic maps is a potential model for cryptography and other applications.

A novel construction of substitution box using a combination of chaotic maps with improved chaotic range

The influential application of substitution boxes in secure communication and multimedia security attracted researchers to construct more robust substitution boxes. The advantage of using chaos in the secure communication is to get additional unpredictability and randomness in data. In this paper, substitution boxes are constructed with the help of chaotic system and linear fractional transformation. The 256 distinct values of each substitution box are then checked with the help of different available algebraic and statistical analyses. These tests evaluate the strength and application of substitution boxes in different encryption techniques. The results indicate the strength of anticipated technique.

An RGB image encryption using diffusion process associated with chaotic map

Image encryption and decryption are essential for securing images from various types of security attacks. In this paper, we have proposed a new algorithm for RGB image encryption and decryption using diffusion method with a combination of chaotic maps. We have formulated a new algorithm for the entire possible range to choose keys for encrypting and decrypting RGB image. Computer simulation with two standard examples and results are given to analyse the capability of the proposed approach. Several important analysis like key space, key sensitivity, NPCR, UACI, MSE and PSNR analysis are performed. Results of various analysis and computer simulation confirm that the new algorithm offers high security and is suitable for practical image encryption.