Henon Chaotic Map Research Articles

Novel grayscale image encryption based on 4D fractional-order hyperchaotic system, 2D Henon map and knight tour algorithm

With the increasing frequency of data exchange, the security of transmitted information, especially images, has become paramount. This paper proposes a novel algorithm for encrypting grayscale images of any dimension by using a proposed fractional-order (FO) 4D hyperchaotic system, 2D Henon chaotic map permutation, and the knight tour algorithm. Initially, chaotic sequences are generated by utilizing the proposed FO 4D hyperchaotic system, which are later employed to rearrange and shuffle the entire image pixels to bolster the efficacy of image encryption. To introduce an additional layer of diffusion, 2D Henon chaotic map permutation is used. Furthermore, the knight tour algorithm is applied by starting from a chosen point and executing specified rounds on the scrambled image to increase the encryption’s robustness. The resultant image encryption algorithm undergoes thorough testing and evaluation. It exhibits high sensitivity to the encryption key and boasts a larger key space, rendering it more resistant to brute-force attacks. The proposed algorithm demonstrates an approximate correlation of 0 between adjacent pixels. Further, encryption of a grayscale image of size 256 × 256 takes approximately 0.4 seconds, rendering it more suitable for cryptographic purposes.

Secure transmission and monitoring of ECG signals based on chaotic mapping algorithms

ABSTRACT The rapid advancement of digital healthcare and telemedicine has accentuated the need for robust and secure methods of transmitting sensitive medical data, such as electrocardiogram (ECG) signals. This article presents an innovative approach to ECG signal encryption, leveraging the power of chaotic dynamics through the Henon and Baker maps. Chaotic systems have proven to be formidable tools for encryption due to their inherent unpredictability and sensitivity to initial conditions. In this study, we demonstrate the efficacy of Chaotic Henon Map (CHM) and Chaotic Baker Maps (CBM) in encrypting ECG data, ensuring both data privacy and integrity during transmission. Through a detailed exploration of the CHM and CBM, we elucidate their mathematical foundations and unique properties that make them suitable for ECG encryption. The encryption process involves the generation of chaotic keys, which are utilized to scramble the ECG signal in a way that is virtually impossible to decipher without the correct decryption keys. We also discuss the security features of this encryption method, including resistance against common cryptographic attacks. The results of our experiments demonstrate the robustness of this encryption technique in safeguarding sensitive medical information, making it a valuable addition to the toolkit of secure ECG data transmission methods.

Innovative chaotic dragon fractal (ChDrFr) shapes for efficient encryption applications: a new highly secure image encryption algorithm

In this paper, the generation of new dragon fractal shapes with chaotic iteration parameters is introduced as the main component of a new efficient approach for different cryptographic applications. This process involves applying a chaotic map, which is considered the initiator pattern, to generate different chaotic dragon fractal (ChDrFr) shapes in lieu of lines (which are classically used to generate dragon fractals). This is the new concept of this paper. The used chaotic maps are sensitive to their initial conditions and are characterized by randomness; hence, the resulting scheme is highly secure. As the resulting ChDrFr shapes have sparse structures, the spaces are packed with random values generated from another 5D hyper chaotic map. For encryption applications based on the substitution approach, one of the five generated ChFrDr shapes can be used to construct a chaotic fractal (ChFr) S-Box, while the other four ChDrFr shapes can be used for diffusion purposes. As an application to these new ChDrFr shapes and the ChFr S-Box, we introduce in this paper a new highly secure image encryption algorithm. A Henon chaotic map is used as the initiator of the ChDrFr shapes. The integer wavelet transform (IWT) is used to generate an approximation and three detail sub-bands for the original image. As the approximation sub-band contains a considerable amount of information about the original image, the above-described ChFr S-Box is used as a replacement for each pixel’s value in this sub-band. Then, the resultant substituted image is diffused with one of the generated ChFrDr shapes. The other three ChDrFr shapes are XORed with the details sub-images. Numerical simulation is applied to ensure the efficacy of encrypted images against different attacks. In particular, the correlation coefficient between the initial and the generated images is shown to be nearly zero. Moreover, tests reveal that the information entropy of the encrypted images and UACI were close to their optimum values. The properties of the newly proposed ChDrFr-based encryption algorithm are compared to the ones obtained by other encryption algorithms, and the results prove the superiority of this newly proposed algorithm to other types of encryption methods.

Reversibly selective encryption for medical images based on coupled chaotic maps and steganography

The security and confidentiality of medical images are of utmost importance due to frequent issues such as leakage, theft, and tampering during transmission and storage, which seriously impact patient privacy. Traditional encryption techniques applied to entire images have proven to be ineffective in guaranteeing timely encryption and preserving the privacy of organ regions separated from the background. In response, this study proposes a specialized and efficient local image encryption algorithm for the medical field. The proposed encryption algorithm focuses on the regions of interest (ROI) within massive medical images. Initially, the Laplacian of Gaussian operator and the outer boundary tracking algorithm are employed to extract the binary image and achieve ROI edge extraction. Subsequently, the image is divided into ROI and ROB (regions outside ROI). The ROI is transformed into a row vector and rearranged using the Lorenz hyperchaotic system. The rearranged sequence is XOR with the random sequence generated by the Henon chaotic map. Next, the encrypted sequence is arranged according to the location of the ROI region and recombined with the unencrypted ROB to obtain the complete encrypted image. Finally, the least significant bit algorithm controlled by the key is used to embed binary image into the encrypted image to ensure lossless decryption of the medical images. Experimental verification demonstrates that the proposed selective encryption algorithm for massive medical images offers relatively ideal security and higher encryption efficiency. This algorithm addresses the privacy concerns and challenges faced in the medical field and contributes to the secure transmission and storage of massive medical images.

An image encryption approach using tuned Henon chaotic map and evolutionary algorithm

An image encryption approach using tuned Henon chaotic map and evolutionary algorithm

Dual Image Cryptosystem Using Henon Map and Discrete Fourier Transform

This paper introduces an efficient image cryptography system. The proposed image cryptography system is based on employing the two-dimensional (2D) chaotic henon map (CHM) in the Discrete Fourier Transform (DFT). The proposed DFT-based CHM image cryptography has two procedures which are the encryption and decryption procedures. In the proposed DFT-based CHM image cryptography, the confusion is employed using the CHM while the diffusion is realized using the DFT. So, the proposed DFT-based CHM image cryptography achieves both confusion and diffusion characteristics. The encryption procedure starts by applying the DFT on the image then the DFT transformed image is scrambled using the CHM and the inverse DFT is applied to get the finally encrypted image. The decryption procedure follows the inverse procedure of encryption. The proposed DFT-based CHM image cryptography system is examined using a set of security tests like statistical tests, entropy tests, differential tests, and sensitivity tests. The obtained results confirm and ensure the superiority of the proposed DFT-based CHM image cryptography system. These outcomes encourage the employment of the proposed DFT-based CHM image cryptography system in real-time image and video applications.

A Chaotic Pulse Train Generator Based on Henon Map

The Henon map forms one of the most-studied two-dimensional discrete-time dynamical systems that exhibits chaotic behavior. The Henon map takes a point in the plane and maps it to a new point . In this paper, a chaotic pulse generator based on the chaotic Henon map is proposed. It consists of a Henon map function subcircuit to realize the Henon map and another subcircuit to perform the iterative operation. The Henon map subcircuit comprises operational amplifiers, multipliers, delay elements and resistors, whereas, the iterative subcircuit is implemented with a simple design that comprises of an edge forming circuit followed by a monostable multivibrator and a voltage controlled switch without the use of any clock control. The proposed design can be used to realize the Henon map and also to generate a chaotic pulse train, with a controllable time interval and pulse position. The proposed circuit is implemented and simulated using Multisim 13.0 and MATLAB R2019b. The chaotic nature of the generated pulse train and also the time interval between the consecutive pulses is verified by the calculation of its Lyapunov exponents.

Chaotic honey badger algorithm for single and double photovoltaic cell/module

PV cell/module/characteristic array accuracy is mainly influenced by their circuit elements, based on established circuit characteristics, under varied radiation and temperature operating conditions. As a result, this study provides a modified accessible Honey Badger algorithm (HBA) to identify the trustworthy parameters of diode models for various PV cells and modules. This approach relies on modifying the 2D chaotic Henon map settings to improve HBA’s searching ability. A series of experiments are done utilizing the RTC France cell and SLP080 solar module datasets for the single and double-diode models to validate the performance of the presented technique. It is also compared to other state-of-the-art methods. Furthermore, a variety of statistical and non-parametric tests are used. The findings reveal that the suggested method outperforms competing strategies regarding accuracy, consistency, and convergence rate. Moreover, the primary outcomes clarify the superiority of the proposed modified optimizer in determining accurate parameters that provide a high matching between the estimated and the measured datasets.

Parameters estimation of three-diode photovoltaic model using fractional-order Harris Hawks optimization algorithm

Effective and efficient systems that calculate the parameters of PV models to be optimal have attracted great interest from many researchers. In this study, a novel algorithm approach is proposed to improve the search performance of the Harris Hawks optimization (HHO) algorithm based on fractal maps. The random parameter that is effective in besiege of the prey in the exploration and exploitation stages of the HHO algorithm is adjusted using the fractal henon chaotic map. Unimodal, multimodal and fixed-dimension benchmark functions were used to verify the quality and efficiency of the proposed Fractional Henon Chaotic Harris Hawks Optimization (FCHHHO) algorithms and variants in providing optimal solutions. Moreover, RTC France photovoltaic cell and Photowatt-PWP 201 photovoltaic models with single, double and three-diodes have been determined accurately, stably and reliably. Comparative and statistical results obtained from the developed algorithms showed that the algorithms have superior performance with regard to accuracy and robustness in comparison with their variants and compared with other metaheuristic algorithms.

A Review on Audio Encryption Using Chaotic Sequences and Finite Field

Audio data are used in various fields such as education, engineering, mathematics, art, advertisement, military, medicine, scientific research, and many more. This excessive growth of audio data boosts the importance of multimedia data processing tools and digital documentation. This access to multimedia data through the internet has created inappropriate prospects which are hazardous for the confidentiality and integrity of the data. To encounter these threats, the domain of audio data security gains broad attention. A considerable number of algorithms have been established to protect personal information over open networks. Finite fields are well-studied algebraic structures with enormous efficient properties which have applications in the fields of cryptology and coding theory. Here, an existing system uses lossless binary Galois field extension based efficient algorithm for audio data encryption. The architecture hired a special type of curve in the diffusion module which depends on efficient elliptic curve arithmetic operations. So, it generates pseudo-random numbers (PRN) and with slight computational efforts, it produces optimum diffusion in the encrypted multimedia files. The method is compared with the proposed system using a scheme uses Henon chaotic map and 128-bit AES secret key in order to generate the cipher audio data. Henon chaotic map is a two dimensional iterated discrete dynamic system that shows chaotic character on specific values of the constants used. Chaotic maps are very sensitive to the initial parameters, i.e., a slight change in the initial conditions drastically changes the overall output generated by the chaotic system. The investigational outcomes through different analyses and time complexity demonstrated the ability of the techniques to counter various attacks. Furthermore, two schemes are compared and more appropriate to be applied for data security.

A novel multiple grayscale image encryption method based on 3D bit-scrambling and diffusion

Since a large number of digital images are shared widely in our daily life, the demand and need for multiple-image encryption algorithms are increasing to ensure the security of the shared images. To present a new perspective to this request, a secure multiple-image encryption method based on 3D bit-scrambling and diffusion operations is proposed for grayscale images in this paper. A three-dimensional bit array is created by extending the eight bit planes of each grayscale image to a third dimension. This 3D bit array is pseudo-randomly scrambled by changing the order of the rows, columns, and layers. The scrambled bit planes are then used to reconstruct the shuffled images. A controlled diffusion operation is also applied to the shuffled and merged images. Both scrambling and diffusion parameters are obtained separately by iterating the chaotic Henon map twice. The initial values of the Henon map are plain images dependent. Several performance analyses including key space and sensitivity, histogram, correlation, entropy, differential, data loss, noise, and running time are carried out to test the proposed method’s resistance against various cryptanalytic attacks. Simulation results show that the proposed method can encrypt multiple images effectively and securely.

An Effective Color Image Encryption Based on Henon Map, Tent Chaotic Map, and Orthogonal Matrices.

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.

Image cryptosystem based on modified Henon chaotic map and dynamic encoding mechanism

Image cryptosystem based on modified Henon chaotic map and dynamic encoding mechanism

Chaos-Based Fast Image Encryption Scheme with Double Zigzag Permutation and Secure SHA256

Encryption is generally used to protect the content of images. This paper proposes a simple chaos-based color image encryption algorithm with permutation and diffusion stages dependent on the plain image to increase plain text sensitivity by collaboratively leveraging a sampled random noise signal, SHA-256, Henon chaotic map, double zigzag scanning and Lorenz system. Specifically, a hash value of the plain image and a sampled true random noise signal are generated using SHA-256 hash function and considered as an initial one-time key, which is then used to locate values from the sampled true random noise signal array to define the initial values and parameters for chaotic Henon map and Lorenz system. The Henon chaotic map creates an output that defines the starting point for double zigzag pixel scanning in the permutation stage, whereas the Lorenz system generates three sequences to diffuse the image’s three components; red, green, and blue using the XOR operation in order to get an encrypted image. Finally, statistical analysis results are offered to evaluate the complexity and ascertain security functionality for the proposed algorithm. Results show that the proposed image encryption algorithm is superior in comparison to other existing algorithms.

A Hybrid Method for the Fault Diagnosis of Onboard Traction Transformers

As vital equipment in high-speed train power supply systems, the failure of onboard traction transformers affect the safe and stable operation of the trains. To diagnose faults in onboard traction transformers, this paper proposes a hybrid optimization method based on quickly and accurately using support vector machines (SVMs) as fault diagnosis systems for onboard traction transformers, which can accurately locate and analyze faults. Considering the limitations of traditional transformers for identifying faults, this study used kernel principal component analysis (KPCA) to analyze the feature quantity of dissolved gas analysis (DGA) data, electrical test data, and oil quality test data. The improved seagull optimization algorithm (ISOA) was used to optimize the SVM, and a Henon chaotic map was introduced to initialize the population. Combined with differential evolution (DE) based on the adaptive formula, the foraging formula of the seagull optimization algorithm (SOA) was improved to increase the diversity of the algorithm and enhance its ability to find the optimal parameters of SVM, which made the simulation results more accurate. Finally, the KPCA–ADESOA–SVM model was constructed and applied to fault diagnosis for the traction transformer. The example analysis compared the diagnosis results of the proposed diagnosis model with those of the traditional diagnosis model, showing further optimization of the feature quantity and improvements in the diagnosis accuracy. This proves that the proposed diagnosis model has high generalization performance and can effectively increase the fault diagnosis accuracy and speed of traction transformers.

Optimized Chaotic encrypted image based on continuous raster scan method

As the greatest effective method of protection of multimedia data is image encryption is extensively used in data hiding, security authentication and content protection. Nevertheless, the security and efficiency are still the key issues of image encryption algorithm. However, the existing image encryption techniques face the issues namely poor resistance to plaintext attacks, simple algorithmic structures and small key space. In order to overcome the problem of traditional techniques, a joint image encryption techniques of continuous raster Scan, Henon Chaotic Map and Chebyshev Chaotic Map are developed for providing a security of images. Initially, the continuous raster is used to scramble the pixels of each blocks, where images are partitioning an image into non overlapping blocks and starting point is randomly selected in Henon Chaotic Map to permute the block. To calculate a random matrix, Chebyshev Chaotic Map is used to generate the sequence based on the secret keys. Finally, bitwise XOR operation between the scrambled image and random matrix is conducted to obtain the encrypted image. The proposed method takes very less time for encryption. Simulation results show that the algorithm is efficient and usable for the security of the image encryption system.

Crypto-Watermarking Algorithm Using Weber’s Law and AES: A View to Transfer Safe Medical Image

We propose a novel method for medical image watermarking in the DCT domain using the AES encryption algorithm. First, we decompose the original medical image into subblocks of 8 × 8. Besides, we apply the DCT and the quantization, respectively, to each subblock. However, in the DCT domain, an adequate choice of the DCT coefficients according to the quantization table in the middle frequencies band is performed. After that, we embed the patient’s data into the corresponding medical image. The insertion step is carried out just after the quantization phase. To increase the robustness, we encrypt the watermarked medical images by using the AES algorithm based on chaotic technique. Arnold’s cat map is used to shuffle the pixel values, and a chaotic Henon map is utilized to generate an aleatory sequence for the AES algorithm. The shuffled watermarked image is encrypted using the modified AES algorithm. The constant of Weber is used to choose the suitable visibility factor for embedding a watermark with high robustness. To control identification, after application of attacks, we use the serial turbo code for correction of the watermark to recover the data inserted. The average peak signal-to-noise ratio (PSNR) of the medical images obtained is 61,7769 dB. Experimental results demonstrate the robustness of the proposed schema against various types of attacks.

A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations

Medical images possess significant importance in diagnostics when it comes to healthcare systems. These images contain confidential and sensitive information such as patients’ X-rays, ultrasounds, computed tomography scans, brain images, and magnetic resonance imaging. However, the low security of communication channels and the loopholes in storage systems of hospitals or medical centres put these images at risk of being accessed by unauthorized users who illegally exploit them for non-diagnostic purposes. In addition to improving the security of communication channels and storage systems, image encryption is a popular strategy adopted to ensure the safety of medical images against unauthorized access. In this work, we propose a lightweight cryptosystem based on Henon chaotic map, Brownian motion, and Chen’s chaotic system to encrypt medical images with elevated security. The efficiency of the proposed system is proved in terms of histogram analysis, adjacent pixels correlation analysis, contrast analysis, homogeneity analysis, energy analysis, NIST analysis, mean square error, information entropy, number of pixels changing rate, unified average changing intensity, peak to signal noise ratio and time complexity. The experimental results show that the proposed cryptosystem is a lightweight approach that can achieve the desired security level for encrypting confidential image-based patients’ information.

An image encryption scheme in bit plane content using Henon map based generated edge map

At present times the topic of Chaos gain a lot of attention for the encryption/decryption methodology, yet we didn’t settled to get a good difference between conventional counterparts. Several chaotic maps can be considered sensitivity dependence to seed values. Taking into consideration for this property, In this paper, the author have presented an image encryption technique employing a 2-dimensional chaotic Henon map, initially it implemented the confusion scheme using chaotic sequence obtained by several iterations using chaotic map approach. In the subsequent stage Edge Maps, generated by edge detection filters and binary bit plane decomposition is applied to perform further confusion using a bit-xor operation to get a cipher image. It is more secure and robust, experimental analysis and simulation is performed to get required results which better revealed that the encrypted images are secured and tolerant to different attacks.

An efficient image encryption scheme using elementary cellular automata with novel permutation box

Digital image communication over public networks requires a high level of security to protect picture elements that represent information. Security is an important and challenging issue that can be solved using cryptography techniques. Generally, image encryption techniques are based on multiple rounds and iterations. In this paper, a secured lightweight cryptosystem is designed based on lookup table operations that reduce computational overhead, resource requirement and power consumption compared to traditional security mechanisms. In this context, one-dimensional elementary cellular automaton has been combined with Henon chaotic map to design a cryptosystem, which can produce unprecedented results in cryptography. Initially, state attractors for rule space are investigated and analyzed in Wolfram’s cellular automata to extract the properties and functional abilities to perform cryptographic operations. A novel algorithm of keyed transposition cipher is applied to digital image in P-Box module to produce shuffled image. Then, the extracted properties of ECA are preserved in a tabular form and further used in the diffusion process. Based on the simulation and comparison with other existing mechanisms, it is evident that the proposed algorithm is promising and obstructive to all kinds of statistical attacks, and it yields security primacy in various areas of cryptography. Encryption/Decryption is based on indexed based lookup tables principal using ECA and can be easily implemented using logic gates. The proposed algorithm provides confidentiality and can be adopted in IoT networks that require lightweight cryptography modules. Experimental results of color and gray images demonstrate flourishing results in the real-time environment of cryptography.