Optimized Image Encryption Model based on Hybridization of Chaotic Maps with Metaheuristic OOBO Algorithm

The main purpose of the proposed image encryption (IE) method is to enhance various security characteristics to protect sensitive images on the internet. In the literature, chaotic maps are preferred for image encryption because of their high randomness and sensitivity to initial parameter values. Therefore, metaheuristic algorithms have been utilized to fine-tune the parameters. In this research, we have employed the metaheuristic Lyrebird optimization (LO) algorithm to fine-tune the chaotic map parameters. The LO algorithm is chosen over other algorithms due to its better exploration and exploitation rate to search for the best solution. The LO algorithm searches for the best parameter value based on the objective function. This research involves the formulation of a multi-objective function that incorporates numerous security parameters, namely, entropy and correlation coefficient (CC), to improve the security attributes of the IE model. The proposed IE model has two steps. In the first step, a random key is generated to transform the pixels of the secret image, whereas in the second step, the image pixels are shuffled based on the shuffling index values to reduce the correlation among the neighboring pixels. In both steps, we have used the chaotic logistic map. The proposed IE is evaluated against statistical and differential attacks on the standard dataset by considering the various images and their different resolutions. The uniform distribution of the histogram of the encrypted images is validated using the chi-square test. Besides that, entropy analysis shows that the average entropy value is 7.9973, 7.9993, and 7.9998 for 256x256, 512x512, and 1024x1024 image resolutions. The average CC and SSIM are near zero value. The average NPCR value (>0.9969) is near the 1 value. Finally, the comparative analysis based on entropy, CC, and NPCR parameters shows that the proposed IE model outperforms the existing models.

Image encryption has been an attractive research field in recent years. The chaos-based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques. This paper proposes a novel image encryption scheme, which is based on the chaotic tent map. Image encryption systems based on such map show some better performances. Firstly, the chaotic tent map is modified to generate chaotic key stream that is more suitable for image encryption. Secondly, the chaos-based key stream is generated by a 1-D chaotic tent map, which has a better performance in terms of randomness properties and security level. The performance and security analysis of the proposed image encryption scheme is performed using well-known ways. The results of the fail-safe analysis are inspiring, and it can be concluded that the proposed scheme is efficient and secure.

In the last decade, the communication of images through the internet has increased. Due to the growing demands for data transfer through images, protection of data and safe communication is very important. For this purpose, many encryption techniques have been designed and developed. New and secured encryption schemes based on chaos theory have introduced methods for secure as well as fast communication. A modified image encryption process is proposed in this work with chaotic maps and orthogonal matrix in Hill cipher. Image encryption involves three phases. In the first phase, a chaotic Henon map is used for permuting the digital image. In the second phase, a Hill cipher is used whose encryption key is generated by an orthogonal matrix which further is produced from the equation of the plane. In the third phase, a sequence is generated by a chaotic tent map which is later XORed. Chaotic maps play an important role in the encryption process. To deal with the issues of fast and highly secured image processing, the prominent properties of non-periodical movement and non-convergence of chaotic theory play an important role. The proposed scheme is resistant to different attacks on the cipher image. Different tests have been applied to evaluate the proposed technique. The results of the tests such as key space analysis, key sensitivity analysis, and information entropy, histogram correlation of the adjacent pixels, number of pixel change rate (NPCR), peak signal to noise ratio (PSNR), and unified average changing intensity (UCAI) showed that our proposed scheme is an efficient encryption technique. The proposed approach is also compared with some state-of-the-art image encryption techniques. In the view of statistical analysis, we claim that our proposed encryption algorithm is secured.

New method for fingerprint images encryption using DNA sequence and chaotic tent map

This paper contrasts the implementation of several chaos-based digital image watermarking techniques in terms of imperceptibility, robustness, security and complexity. Most spatial and transform domains methods have been used namely Least Significant Bit (LSB), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Redundant Discrete Wavelet Transform (RDWT) with Singular Value Decomposition (SVD) mathematical tool which has enhanced embedding capability. Both continuous and discrete chaotic maps namely Arnold's Chaotic Map (ACM), Logistic Chaotic map (LCM) and Lorenz Chaotic Map (LoCM) are included to result in secure schemes. Exhaustive series of tests have been performed along with a range of evaluation metrics for imperceptibility evaluation. In addition, Robustness of all the techniques has also been confirmed by applying a variety of attacks on the resulting images. This study will help to adopt the most suitable methods for a given application as sufficient number of test images have been utilized.

A simplified and efficient technique of cryptography of an image will be developed. The technique will utilize two simple rounds to apply image encryption and decryption, each round will be implemented by performing a simple rows shuffling and columns shuffling, eliminating the need for computational logical and arithmetic operations required for other techniques of image encryption. Our approach, while simplifying computational demands by eliminating complex arithmetic and logical operations, maintains robust security through the integration of dual Chaotic Logistic Map Models (CLMM) to generate highly sensitive indices keys. These indices keys control row and column shuffling, which provides a high degree of permutation and resists known-plaintext and cipher text-only attacks. The technique will require two secret indices keys, these keys will be variable in the length and the contents and they will depend on the image to be encrypted-decrypted, generation of these keys will be very easy and simple. The shuffling operations will be implemented using two secret indices keys, and by implementing couple of chaotic logistic map these keys will be produced using selected chaotic parameters values included in the private key. The technique uses a 256-bit private key, chaotic logistic maps, and high sensitivity to parameter variations to achieve "Very strong" key space entropy, with encryption throughput of 19,540 KB/s and robust performance across diverse image sizes. The generated decrypted image may become so sensitive to chosen of private key values, and any little variation in the private key through the decryption task, it will be showed as a hacking try. The proposed technique will be flexible, it will be used to process every image with any size (gray and/or color), and image changing will not require any updating in the decryption and encryption processes. The developed technique will be efficient; it will decrease both the encryption and decryption times, and it lead to accelerate the image encryption process comparing with other techniques. The study systematically utilizes specific evaluation metrics to substantiate claims regarding the quality, security, and velocity of the proposed cryptographic technique. Quality is assessed by Mean Square Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) metrics

This manuscript is about a modified image encryption algorithm based on coupled map lattices and substitution box transformation. The places of the pixels of image are mix up by using chaotic tent map and after that employing delayed coupled map lattices and S-box transformation to puzzle the association between the original image and the encrypted image. The simulation results validate that the propose technique possesses better strength for realistic image encryption.

Structural damage identification based on metaheuristic algorithms is an important part of structural health monitoring with great potential. However, the metaheuristic intelligent algorithms probably have flaws of slow convergence speed and low calculation accuracy, which need to be improved to address engineering optimization problems. In this paper, the black widow optimization (BWO) algorithm is used for structural damage identification. In addition, a multistrategy fusion–improved BWO (IBWO) algorithm is proposed by introducing the tent chaotic mapping, the golden sine equation, the gazelle wandering equation, and the boundary treatments. First, in the population initialization stage, tent chaotic mapping is introduced to improve the quality of the initial solution. Second, the golden sine strategy is used to acquire the optimal solution quickly in local search. Then, the motion equation of the gazelle algorithm is employed to enhance the global search ability and avoid the algorithm falling into the local optimal solution. Finally, the boundary processing strategy is presented to reduce the calculation of solutions and improve the optimization efficiency. A novel damage identification objective function is redefined by combining the modal assurance criterion and the modal flexibility. Then, a two‐story rigid frame structure is utilized for numerical simulations. Moreover, experimental studies with a simply supported beam were carried out to verify the performance of the proposed damage identification method. Simulation results and experimental studies demonstrate that, even with the interference of strong noise, the IBWO algorithm has a higher accuracy and efficiency in damage identification compared to the BWO algorithm.

The Atomic Search Optimization (ASO) algorithm is an efficient metaheuristic algorithm inspired by molecular-based dynamics. Although it effectively solves numerous engineering design optimization problems, the algorithm still has drawbacks, such as premature convergence and an imbalance between exploration and exploitation. This paper proposes an improved Atomic Search Optimization Algorithm (TGD_ASO) with a genetic mutation mechanism, golden sine strategy, and chaotic mapping. Firstly, the Tent chaotic mapping is introduced to improve the population diversity of the algorithm, thereby enhancing the search space. Secondly, the golden sine strategy is utilized to strengthen global search efficiency. After that, we introduce the random variation and crossover operations in differential evolutionary algorithms to perturb the updated positions to help the atoms jump out of the local optimum and improve the population’s diversity and the algorithm’s accuracy. To validate and test the performance of the proposed TGD_ASO algorithm. We analyze the performance of the TGD_ASO algorithm on the CEC2017 benchmarks and six real design issues. In the CEC2017 benchmark test, the algorithm achieved 23 and 22 top positions in the 30 and 50 dimensions, respectively. Its performance significantly surpassed that of the ASO algorithm. Experimental data applied to engineering design problems have shown that the algorithm achieved 5 key outcomes. The algorithm also significantly outperforms metaheuristic algorithms such as ASO in terms of convergence time, accuracy, stability, and optimization ability.

The sparrow search algorithm (SSA) is a newly proposed meta-heuristic optimization algorithm based on the sparrow foraging principle. Similar to other meta-heuristic algorithms, SSA has problems such as slow convergence speed and difficulty in jumping out of the local optimum. In order to overcome these shortcomings, a chaotic sparrow search algorithm based on logarithmic spiral strategy and adaptive step strategy (CLSSA) is proposed in this paper. Firstly, in order to balance the exploration and exploitation ability of the algorithm, chaotic mapping is introduced to adjust the main parameters of SSA. Secondly, in order to improve the diversity of the population and enhance the search of the surrounding space, the logarithmic spiral strategy is introduced to improve the sparrow search mechanism. Finally, the adaptive step strategy is introduced to better control the process of algorithm exploitation and exploration. The best chaotic map is determined by different test functions, and the CLSSA with the best chaotic map is applied to solve 23 benchmark functions and 3 classical engineering problems. The simulation results show that the iterative map is the best chaotic map, and CLSSA is efficient and useful for engineering problems, which is better than all comparison algorithms.

ABSTRACTThe transient electromagnetic method (TEM) is a prominent geophysical technique, and the TEM inversion for resistivity models is a crucial aspect of physical exploration. However, TEM inversion faces challenges such as nonlinearity, multiple solutions and ill‐conditioning, which can lead to inaccurate results. In response to these challenges, metaheuristic algorithms have been extensively studied for their innovative approaches to solving inverse problems. Despite this, many existing metaheuristic inversion algorithms exhibit limitations, including premature convergence, slow convergence speed and inadequate computational accuracy. To address these issues, an improved bat algorithm (IBA) that incorporates logistic chaotic mapping and a spiral flight strategy (Logistic Chaotic Mapping and Spiral Flight Strategy‐Based Bat Algorithm, LSBA) has been proposed. The logistic chaotic mapping strategy is utilized to initialize the population of the bat algorithm to enhance the initial convergence rate. Moreover, the spiral flight strategy facilitates the bats’ escape from local optima, thereby improving the algorithm's local exploration capabilities and solution accuracy. Numerical simulations, synthetic models and field experiments have demonstrated that the LSBA significantly enhances solution precision (the degree of closeness between the algorithm's inverted parameters and the true values), convergence speed and anti‐noise performance. The LSBA effectively retrieves the stratigraphic parameters of the true model and accurately represents the geological information of actual mining areas, thereby validating the efficacy and feasibility of the proposed approach in TEM inversion.

Communication is essential to every society, and securely exchanging data are critical in the age of digital data. The image has been the center of interest for security; chaotic maps image encryption become widely used in recent years. In our study, authors assessed the pixel rearrangement (permutation) and pixel dissemination (diffusion) stage used in cipher image established on designed scheme Pseudo-random number Generators (PRNGs) and Logistic chaotic map. Logistic maps used to generate seed value for PRNG and two-permutation stage and PRNGs used in diffusion operation. The proposed design through experimental tests demonstrate decent Statistical output, and high security for our image encryption schema, Our PRNGs passed NIST SP 800-22, and TestU01 practical randomness test suggests PRNGs have suitable statistical property.

Chaos and compressive sensing based novel image encryption scheme

This paper shows a digital noise generator designed in FPGA, based on a variant of the one‐dimensional (1D) chaotic tent map (T‐1D). The T‐1D map is a piecewise linear 1D chaotic map that defines the statistical behavior of the generated sequences using its control parameter. In this way, the proposed noise generator is a highly competitive alternative in cryptographic systems when the statistical behavior of the sequences is closer to the uniform statistical distribution. The proposed system uses the inverted tent chaotic map (IT‐1D), which has the same statistical behavior as the T‐1D map. The fundamental algorithm used in this system was developed based on a 64‐bit double precision format according to the numerical representation of floating point numbers defined in the IEEE‐754 standard. The proposed system is analized using mechanical statistic tools and some statistical tests defined in the NIST 800‐22SP (USA) standard. The main contribution of this work is the possibility of generating binary sequence of pseudorandom appearance by a procedure implemented in an FPGA device that translates real numbers to natural numbers preserving the statistical properties of sequences of real numbers that can be generated with the tent chaotic map in its original definition domain.

Image encryption based on chaotic maps is an important method for ensuring the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed that employs a compound chaotic map and random cyclic shift. First, a new hybrid chaotic system is designed by coupling logistic, ICMIC, Tent, and Chebyshev (HLITC) maps. Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and approximate entropy illustrate that the new hybrid chaotic map has better chaotic performance. Then, the proposed HLITC chaotic system and spiral transformation are used to develop a new chaotic image encryption scheme using the double permutation strategy. The new HLITC chaotic system is used to generate key sequences used in the image scrambling and diffusion stages. The spiral transformation controlled by the chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments on statistical analysis, key sensitivity, and key space analysis were conducted. Experimental results show that the proposed encryption scheme has good robustness against brute-force attacks, statistical attacks, and differential attacks and is more effective than many existing chaotic image encryption algorithms.