Arnold Cat Research Articles

A new solution for tackling mismatching losses in solar PV array via image encryption

Solar photovoltaic systems may undergo changes in power generation due to environmental factors such as partial shadowing, resulting in losses due to mismatch. This can ultimately lead to a decrease in the efficiency of the system's power conversion. While current solutions are both cost-effective and efficient, there is potential for novel approaches to further enhance system performance by improving consistency, power production, and minimizing mismatch losses. To address these limitations, this paper proposes the utilization of a highly efficient generalized Arnold's cat Map technique, commonly used in the image encryption process, to reconfigure the PV array. The effectiveness of these proposed approaches is evaluated in a MATLAB Simulink environment, specifically for a symmetrical (8x8) PV array, under various benchmark conditions such as Long wide; Short wide, Long Narrow, and Short Narrow shading conditions. The results obtained from these evaluations are then compared to prominent strategies such as Total-cross-tied and the recently reported Chaotic Baker's Map reconfiguration techniques. Furthermore, extensive analysis is conducted using different performance indices to gain a comprehensive understanding of the proposed approaches.

Secure medical image watermarking based on reversible data hiding with Arnold's cat map

The process of restoring medical images to their original form after the extraction process in application watermarking is crucial for ensuring their authenticity. Inaccurate diagnoses can occur due to distortions in medical images from conventional data embedding applications. To address this issue, reversible data hiding (RDH) method has been proposed by several researchers in recent years to embed data in medical images. After the extraction process, images can be restored to their original form with a reversible data-hiding method. In the past few years, several RDH methods have been rapidly developed, which are based on the concept of difference expansion (DE). However, it is crucial to pay attention to the security of the medical image watermarking method, the embedded data with RDH method can be easily modified, accessed, and altered by unauthorized individuals if they know the employed method. This research suggests a new approach to secure the RDH method through the use of Chaotic Map-based Arnold's Cat Map algorithms on the medical images. Data embedding was performed on random medical images using a DE method. Four gray-scale medical image modalities were used to assess the proposed method's efficacy. In our approach, we can incorporate capacity up to 0.62 bpp while maintaining a visual quality up to 41.02 dB according to PSNR and 0.9900 according to SSIM. The results indicated that it can enhance the security of the RDH method while retaining the ability to embed data and preserving the visual appearance of the medical images.

Robust Watermarking Using FFT and Cordic QR Techniques

Digital media sharing and access in today’s world of the internet is very frequent for every user. The management of digital rights may come into threat easily as the accessibility of data through the internet become wide. Sharing digital information under security procedures can be easily compromised due to the various vulnerabilities floating over the internet. Existing research has been tied to protecting internet channels to ensure the safety of digital data. Researchers have investigated various encryption techniques to prevent digital rights management but certain challenges including external potential attacks cannot be avoided that may give unauthorized access to digital media. The proposed model endorsed the concept of watermarking in digital data to uplift media security and ensure digital rights management. The system provides an efficient procedure to conduct over-watermarking in digital audio signals and confirm the avoidance of ownership of the host data. The proposed technique uses a watermark picture as a signature that has been initially encrypted with Arnold's cat map and cyclic encoding before being embedded. The upper triangular R-matrix component of the energy band was then created by using the Fast Fourier transform and Cordic QR procedures to the host audio stream. Using PN random sequences, the encrypted watermarking image has been embedded in the host audio component of the R-matrix. The same procedure has been applied to extract the watermark image from the watermarked audio. The proposed model evaluates the quality of the watermarked audio and extracted watermark image. The average PSNR of the watermarked audio is found to be 37.01 dB. It has also been seen that the average PSNR, Normal cross-correlation, BER, SSMI (structure similarity index matric) value for the extracted watermark image is found to be 96.30 dB, 0.9042 units, 0.1033 units, and 0.9836 units respectively. Further, the model has been tested using various attacks to check its robustness. After applying attacks such as noising, filtering, cropping, and resampling on the watermarked audio, the watermark image has been extricated and its quality has been checked under the standard parameters. It has been found that the quality of the recovered watermark image satisfying enough to justify the digital ownership of the host audio. Hence, the proposed watermarking model attains a perfect balance between imperceptibility, payload, and robustness.

Medical image encryption using multi chaotic maps

Over the last twenty years, chaos-based encryption has been an increasingly popular way to encrypt and decrypt data using nonlinear dynamics and deterministic chaos. Discrete chaotic systems based on iterative maps have gotten a lot of interest because of their simplicity and speed. In this paper, three kinds of chaotic maps are utilized to build a digital image encryption strategy depending on a chaotic system. These chaotic maps are the logistic map, Arnold Cat’s map, and Baker’s map. In addition to using the triple data encryption standard (3DES) encryption scheme with the chaotic maps mentioned. The results of the experiments revealed that the suggested digital image encryption technique is both efficient and secure, making it ideal for usage in insecure networks. The transmission control protocol (TCP)/internet protocol (IP) protocol was used for the purpose of transferring data from server to client through the network and vice versa.

EGPIECLMAC: efficient grayscale privacy image encryption with chaos logistics maps and Arnold Cat

EGPIECLMAC: efficient grayscale privacy image encryption with chaos logistics maps and Arnold Cat

Robust Chaos-Based Medical Image Cryptosystem

In In this paper, we propose an efficient cryptosystem for medical images. While the confusion stage is ensured by an Arnold's cat map allowing the permutation of pixels; the diffusion stage is alleviated by an improved logistic map used by the chaotic key-based algorithm (CKBA). The simulation results attest that the proposed algorithm has superior security and enables efficient encryption/decryption of medical images. Performances were evaluated by several security analyses: the NPCR and UACI are improved over 99.60% and 33.46% respectively, and entropy is reported close to 7.8. What makes this new cipher much stronger security.

A Novel Solar Photovoltaic Array Reconfiguration Technique Using Two-Dimensional Generalized Arnold's Cat Map

Abstract This paper presents a highly efficient image encryption-based Arnold's cat map (ACM) technique to reconfigure the photovoltaic (PV) array to enhance the output and mitigate the mismatch losses due to partial shading (PS). The proposed ACM technique concentrates on alleviating the power loss by effectively dispersing the shade over the entire PV array without modifying its electrical circuitry. The proposed reconfiguration technique is investigated and analyzed with conventional series–parallel and total-cross-tied configurations along with the recently reported chaotic Baker's map, odd–even, odd–even–prime pattern-based configurations. The proposed technique is examined for symmetrical 6 × 6 PV array and unsymmetrical 6 × 9 PV array under distinct nonuniform and uniform PS cases. To confirm the potency and superior performance of the proposed technique, the system has been extensively examined with nine performance parameters such as global maximum power, mismatch power, power loss, efficiency, fill factor, array yield, capacity factor, performance ratio, and the number of maximum power peaks. An experimental setup of a 4 × 4 array reconfiguration system prototype is developed and tested in a real-time environment to validate the effectiveness of the proposed technique over the existing ones. From the comprehensive investigation, it is regarded that the proposed technique offers consistently superior performance with the least percentage mismatch losses and maximum power enhancement of 48.8%, 31.03%, and 27.5% for various shading cases of 6 × 6 and 6 × 9 PV arrays.

Resource Optimized Selective Image Encryption of Medical Images Using Multiple Chaotic Systems

Medical images typically contain personal and diagnostic information about patients and are typically shared among hospitals, doctors, and patients via public networks. As a result, they must be kept secure while being stored and transported to protect the patient's privacy. However, due to the unique qualities of digital image data, such as significant redundancy and correlation between pixels and their huge size, traditional cryptographic techniques are ineffective for providing proper security while encrypting them. The necessity to develop enhanced and specialized image encryption algorithms arise as traditional techniques cease to be a trustworthy option. This problem motivated them to develop many low computational complexity methods to encrypt these medical images. In this research work, Block Cipher based Region of interest medical image encryption with multiple maps is proposed. Primarily, Region of Interest (ROI) regions are extracted with the help of a Laplacian edge detection operator, and then based on the edges in the blocks, the image is classified into wanted (ROI) and unwanted (RONI or ROB) parts. Next, the important ROI regions are permuted circularly with the help of Arnold's cat map and angle value. Then permuted ROI part is encrypted using the duffling system and unimportant regions are unaltered. Finally, the ROI encrypted image is obtained by concating the ROI encrypted part and the Region of Background (ROB) unaltered part. The encryption algorithm proposed has better security performance which is demonstrated in the experiments such as attacks on data loss, differential attacks, statistical attacks, and brute force attacks. These results show that the security in the proposed method is much better than many chaotic encryption algorithms proposed in recent times.

Robustness of Modified Non-Separable HaarWavelet Transform and Singular Value Decomposition for Non-blind Digital Image Watermarking

Security is a matter of significant concern for image media. An effective way to protect images is by digital watermarking. This paper introduces a non-blind digital watermarking scheme using modified non-separable Haar wavelet transform (NSHWT), singular value decomposition (SVD), Arnold's cat map, and Rabin-p cryptosystem to embed a binary watermark image into a color cover image. Aside from robustness, security is also prioritized in the scheme. High robustness is achieved using two transform domain techniques, discrete wavelet transform (DWT) and SVD, while security is heightened with the double encryption by Arnold's cat map scrambling and Rabin-p cryptosystem. A disadvantage of the discrete wavelet transform in digital image watermarking is the calculation complexity and the high cost of changing memory and time. The proposed algorithm uses a modified NSHWT instead of the traditional method of DWT. Therefore, the load of the process on the hardware can significantly be reduced while still maintaining the advantages of DWT. The algorithm is objectively evaluated in terms of imperceptibility, robustness, and embedding capacity for both binary and color watermarks, as well as efficiency. It has been concluded that the proposed scheme performs competently compared with other recent watermarking techniques based on DWT and SVD.

IEHC: An efficient image encryption technique using hybrid chaotic map

Image encryption is essential for the transmission of the sensitive images through insecure channels used in wired or wireless communication nowadays. With the advent of cloud enabled surveillance applications, Internet of Things applications, social media communications, the requirement of image encryption is also increasing day by day. The conventional encryption schemes demand high resources in terms of processing power, memory and bandwidth resulting degradation in overall system response time. In this paper, first a novel shuffling technique has been introduced to shuffle the pixels of an input color image. Subsequently, this paper proposes an image cipher that uses Logistic map and Arnold's cat map for encryption of color images. The experimental results and various security analyses exhibit good security characteristics and also prove its robustness against various types of noises, data loss and cryptanalysis attacks, making it appropriate for implementing in real-time applications.

The Graph Structure of the Generalized Discrete Arnold's Cat Map

Chaotic dynamics is an important source for generating pseudorandom binary sequences (PRBS). Much efforts have been devoted to obtaining period distribution of the generalized discrete Arnold&#x0027;s Cat map in various domains using all kinds of theoretical methods, including Hensel&#x0027;s lifting approach. Diagonalizing the transform matrix of the map, this article gives the explicit formulation of any iteration of the generalized Cat map. Then, its real graph (cycle) structure in any binary arithmetic domain is disclosed. The subtle rules on how the cycles (itself and its distribution) change with the arithmetic precision <inline-formula><tex-math notation="LaTeX">$e$</tex-math><alternatives><mml:math><mml:mi>e</mml:mi></mml:math><inline-graphic xlink:href="li-ieq1-3051387.gif"/></alternatives></inline-formula> are elaborately investigated and proved. The regular and beautiful patterns of Cat map demonstrated in a computer adopting fixed-point arithmetics are rigorously proved and experimentally verified. The results can serve as a benchmark for studying the dynamics of the variants of the Cat map in any domain. In addition, the used methodology can be used to evaluate randomness of PRBS generated by iterating any other maps.

Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data. This paper presents a cancellable multi-biometric identification scheme that includes four stages: biometric data collection and processing, Arnold's Cat Map encryption, decimation process to reduce the size, and final merging of the four biometrics in a single generated template. First, a 2D matrix of size 128 × 128 is created based on Arnold's Cat Map (ACM). The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security. The decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data redundancy. Moreover, some sort of aliasing occurs due to decimation, contributing to the intended distortion of biometric templates. The hybrid structure that comprises encryption, decimation, and merging generates encrypted and distorted cancellable templates. The simulation results obtained for performance evaluation show that the system is safe, reliable, and feasible as it achieves high security in the presence of noise.

Development of an enhanced scatter search algorithm using discrete chaotic Arnold’s cat map

Solving optimization problems is an ever-growing subject with an enormous number of algorithms. Examples of such algorithms are Scatter Search (SS) and genetic algorithms. Modifying and improving of algorithms can be done by adding diversity and guidance to them. Chaotic maps are quite sensitive to the initial point, which means even a very slight change in the value of the initial point would result in a dramatic change of the sequence produced by the chaotic map Arnold's Cat Map. Arnold's Cat Map is a chaotic map technique that provides long non-repetitive random-like sequences. Chaotic maps play an important role in improving evolutionary optimization algorithms and meta-heuristics by avoiding local optima and speeding up the convergence. This paper proposes an implementation of the scatter search algorithm with travelling salesman as a case study, then implements and compares the developed hyper Scatter Arnold's Cat Map Search (SACMS) method against the traditional Scatter Search Algorithm. SACMS is a hyper Scatter Search Algorithm with Arnold's Cat Map Chaotic Algorithm. Scatter Arnold's Cat Map Search shows promising results by decreasing the number of iterations required by the Scatter Search Algorithm to get an optimal solution(s). Travelling Salesman Problem, which is a popular and well-known optimization example, is implemented in this paper to demonstrate the results of the modified algorithm Scatter Arnold's Cat Map Search (SACMS). Implementation of both algorithms is done with the same parameters: population size, number of cities, maximum number of iterations, reference set size, etc. The results show improvement by the modified algorithm in terms of the number of iterations required by SS with an iteration reduction of 10–46 % and improvements in time to obtain solutions with 65 % time reduction

The Möbius phenomenon in Generalized Möbius-Listing surfaces and bodies, and Arnold's Cat phenomenon

The Möbius phenomenon in Generalized Möbius-Listing surfaces and bodies, and Arnold's Cat phenomenon

Medical Image Encryption Scheme Using Multiple Chaotic Maps

Telemedicine and various tele-medicinal applications are revolutionizing a variety of healthcare departments through its innovative means of remote diagnosing and faster first aid administration. Digital images play an important role in these applications for ensuring better and faster health carfigure. These digital images, which usually contain confidential and diagnostic information about the patients, are usually transmitted through public networks among hospitals, doctors and patients. Consequently, there is a need to secure them while being stored and in transit to guarantee the privacy of the patient. However, unique properties of digital image data, such as high redundancy and correlation between the pixels of the image and their large size, make the conventional cryptographical algorithms insufficient for ensuring proper security while encrypting them. As the conventional algorithms seize to be a reliable solution, the need to develop improved and dedicated image encryption algorithms also arises. Chaotic systems are systems that appear random and unpredictable from the outside but are governed by deterministic equations or rules on the inside. Due to these properties, along with ergodicity and its heightened sensitivity to the initial conditions, chaotic systems are devised to be one of the best candidates for securing the storage and transmission of digital images. However, the security of a chaotic image encryption system depends upon the chaotic behavior demonstrated by the chaotic map applied in the image encryption system. Because of this, different attacks can be used to break a chaotic encryption system if the scheme is not well-structured. This paper introduces a chaotic image encryption scheme that incorporates two chaotic maps, namely, Arnold's Cat Map and 2D Logistic-Sine-Coupling Map(2D-LSCM), for increased randomness and security of the encrypted image. We also analyze the performance and security of our scheme and compare it with other prominent chaotic image encryption schemes.

A Hyperbolic Arnold's Cat Map-Based System for Multimedia Data Encryption

Cryptography is one of the most used techniques to secure data since antiquity. It has been largely improved by introducing several mathematical concepts. This paper proposes a new asymmetric cryptography approach using combined Arnold's cat map with hyperbolic function and Chebyshev chaotic map for audio and image encryption. The proposed scheme uses Chebyshev map for public and secrete keys generation and the same equation with Arnold's cat map for encryption and decryption. Hyperbolic functions are also introduced replacing regular integer values in Arnold's map. The results show a good and promising efficiency as well as the theoretical discussion. Several future possible improvements are presented in the conclusion.

A new Grayscale image encryption algorithm composed of logistic mapping, Arnold cat, and image blocking

This paper proposes a new chaotic-based encryption algorithm to encrypt images securely and effectively. A combination of Arnold cat, logistic mapping and image blocking has been used to design this algorithm. The proposed algorithm is a special algorithm that not only does it use image blocking once to relocate the pixels in four areas of the image separately but also uses an Arnold cat mapping to relocate the pixels across the whole image once again. This results in a higher number of pixel relocations which makes it impossible to decode without the key. The other interesting and new point is the particular use of chaotic logistic mapping to develop three image keys and to combine them with the input image, and to develop four other image keys to encrypt the image. Relocation of the input image blocks and the images generated by the logistic mapping are conducted through sorting the numbers generated by the mapping and how they have been relocated. Then, Arnold cat is used to relocate the pixels across the whole image (which is a combination of the input image and three images generated by logistic mapping). Eventually, the encryption operation is conducted on the obtained image using the encryption key (the image generated through the combination of the four keys). Numerous statistical tests and security analyses indicate the excellent security of our proposed algorithm.

X-Ray Images Encryption Analysis Using Arnold's Cat Map and Bose Chaudhuri Hocquenghem Codes

In the medical world, a digital medical image is a requirement for image sharing in which the confidential data of the patient should be protected from unauthorized access. This study proposes a technique that can preserve image confidentiality using image encryption. This approach converts the original image into another shape that can not be visually interpreted, so unauthorized parties can not see an image's substance. This research proposes a method of X-Ray images encryption based on Arnold's Cat Map and Bose Chaudhuri Hocquenghem by shuffling coordinates from the original pixel into new coordinates. The Bose Chaudhuri Hocquenghem encoding scheme strengthens Arnold's cat map encryption by detecting and fixing bits of an image pixel value error. This study comprises results checked by giving the X-Ray or rontgen image noise with distinct variances. These algorithms are supposed to provide decrypted images with high accuracy and are more resistant to attack. Our result showed that the system using Bose Chaudhuri Hocquenghem codes has a better Peak Signal-to-Noise Ratio result equal to infinity and Bit Error Rate, equivalent to 0 at a more significant variance of each form of noise than the process using Arnold's Cat Map codes only. The Brute Force Attack for Bose Chaudhuri Hocquenghem takes 2.86 × 1058 years, while Arnold's Cat Map takes 3.9 × 1011 years, so the Bose Chaudhuri Hocquenghem code is more resistant to Brute Force Attack than the Arnold's Cat Map method.

A New Video Steganography Scheme Based on Shi-Tomasi Corner Detector

Recent developments in the speed of the Internet and information technology have made the rapid exchange of multimedia information possible. However, these developments in technology lead to violations of information security and private information. Digital steganography provides the ability to protect private information that has become essential in the current Internet age. Among all digital media, digital video has become of interest to many researchers due to its high capacity for hiding sensitive data. Numerous video steganography methods have recently been proposed to prevent secret data from being stolen. Nevertheless, these methods have multiple issues related to visual imperceptibly, robustness, and embedding capacity. To tackle these issues, this paper proposes a new approach to video steganography based on the corner point principle and LSBs algorithm. The proposed method first uses Shi-Tomasi algorithm to detect regions of corner points within the cover video frames. Then, it uses 4-LSBs algorithm to hide confidential data inside the identified corner points. Besides, before the embedding process, the proposed method encrypts confidential data using Arnold's cat map method to boost the security level. Experimental results revealed that the proposed method is highly secure and highly invisible, in addition to its satisfactory robustness against Salt & Pepper noise, Speckle noise, and Gaussian noise attacks, which has an average Structural Similarity Index (SSIM) of more than 0.81. Moreover, the results showed that the proposed method outperforms state-of-the-art methods in terms of visual imperceptibility, which offers excellent peak signal-to-noise ratio (PSNR) of average 60.7 dB, maintaining excellent embedding capacity.

Digital Image Cryptography Using Combination of Arnold's Cat Map and Bernoulli Map Based on Chaos Theory

Digital Image Cryptography Using Combination of Arnold's Cat Map and Bernoulli Map Based on Chaos Theory