Henon Map Research Articles

The implementation of algebraic complex lookup tables over non-chain galois ring extensions and henon map in multimedia security

Abstract Image encryption is crucial for web-based data storage and transmission. Complex algebraic structures play a vital role in providing unique features and binary operations. However, current algebraic-based techniques face challenges due to limited key space. To tackle this issue, our study uniquely connects the algebraic structures with a chaotic map. The study introduces a complex non-chain Galois ring structure and a 12-bit substitution box for image substitution. An affine map is utilized to permute image pixels, and the 12-bit substitution box is uniquely mapped to a Galois field for encryption. A two-dimensional Henon map is employed to generate different keys for the XOR operation, resulting in an encrypted image. The resilience of the scheme against various attacks is evaluated using statistical, differential, and quality measures, showcasing its effectiveness against well-known attacks.

OFDM Transmission in Rayleigh Fading Channel for S-Box and 3D Chaotic Maps Based Encrypted Image

Data encryption is an important part of the communication system. The Chaos essential properties, make it a crucial candidate for encryption applications. There is a compromise between complexity and security in previous studies. In this study, high security was achieved with low complexity. This paper proposed a 3D chaotic map and S-Box has been cascaded to get a high efficiency as complex algorithms or multi-iteration schemes. The first stage is ciphering using 3D cat-map, the second stage is S-box based on 3D henon map, while the third stage is another ciphering stage using 3D henon map. In this study, various encryption techniques, including cipher algorithms and substitution box, are combined with the OFDM system to establish a secure image transmission over a Rayleigh fading channel. QPSK modulation is used to ensure the simplicity of the proposed system. Six gray images are used, Lena, the cameraman, Barbara, Baboon, pepper and Elaine for testing and comparing with previous works. Security analysis is performed to evaluate the quality and security of the encryption process, the entropy value reach 7.99, correlation coefficient is around zero and the histogram is uniform. In addition, the key size is 2630. For image transmission evaluation, the PSNR and BER are utilized and it reached 10-5 for BER. According to the statistical results, the proposed image encryption scheme is secure and efficient.

Cutting-Edge Amalgamation of Web 3.0 and Hybrid Chaotic Blockchain Authentication for Healthcare 4.0

Healthcare 4.0 is considered the most promising technology for gathering data from humans and strongly couples with a communication system for precise clinical and diagnosis performance. Though sensor-driven devices have largely made our everyday lives easier, these technologies have been suffering from various security challenges. Because of data breaches and privacy issues, this heightens the demand for a comprehensive healthcare solution. Since most healthcare data are sensitive and valuable and transferred mostly via the Internet, the safety and confidentiality of patient data remain an important concern. To face the security challenges in Healthcare 4.0, Web 3.0 and blockchain technology have been increasingly deployed to resolve the security breaches due to their immutability and decentralized properties. In this research article, a Web 3.0 ensemble hybrid chaotic blockchain framework is proposed for effective and secure authentication in the Healthcare 4.0 industry. The proposed framework uses the Infura Web API, Web 3.0, hybrid chaotic keys, Ganache interfaces, and MongoDB. To allow for more secure authentication, an ensemble of scroll and Henon maps is deployed to formulate the high dynamic hashes during the formation of genesis blocks, and all of the data are backed in the proposed model. The complete framework was tested in Ethereum blockchain using Web 3.0, in which Python 3.19 is used as the major programming tool for developing the different interfaces. Formal analysis is carried out with Burrows–Abadi–Needham Logic (BAN) to assess the cybersecurity reliability of the suggested framework, and NIST standard tests are used for a thorough review. Furthermore, the robustness of the proposed blockchain is also measured and compared with the other secured blockchain frameworks. Experimental results demonstrate that the proposed model exhibited more defensive characteristics against multiple attacks and outperformed the other models in terms of complexity and robustness. Finally, the paper gives a panoramic view of integrating Web 3.0 with the blockchain and the inevitable directions of a secured authentication framework for Healthcare 4.0.

A Quantum Image Secret Sharing Scheme Based on Designated Multi‐Verifier Signature

AbstractThis paper presents a quantum image secret sharing scheme based on designated multi‐verifier signature. First, share images are generated by a 2D hyperchaotic system incorporating sinusoidal mapping, Henon mapping, and Cubic mapping using the cascade modulation method. Quantum Arnold scrambling and diffusion are performed on the secret image. Subsequently, the concept of designated multi‐verifier signature is introduced. In the secret image sharing phase, the pixel values of the share images are used to sign the secret image, and the signed secret image and share images are sent to a trusted third party and designated verifiers, respectively. In this scheme, no carrier images are required, and the share images held by the participants do not contain any information about the secret image. Finally, simulation experiments and security analysis are conducted on IBM Qiskit platform and Matlab software.

Hybrid Block Chaotic Compressive Sensing and Chaotic Scrambling Algorithms for Color Image Encryption System

This paper suggests a new image encryption algorithm based on block compressive sensing (BCS) and chaotic scrambling techniques. With compressive sensing (CS), signals can be sampled much lower than the Nyquist-Shannon rate while preserving their information content. BCS can be used as a one-step process by using a 3D logistic chaotic map, the measurement matrix is used as a secret key for encryption. BCS algorithm used an individual image reconstruction algorithm that leverages l_1norm minimization to promote signal sparsity, and a smoothing operator to enhance image quality. An encrypted image is first decomposed into three sub-images based on the tricolor theory; then, a discrete wavelet transform is used to sparsely process the three decomposed images. A 2D Henon map is used to scramble the compressed image after compression. This process further enhances the security of the system by increasing the complexity of the encryption process. The results showed that the proposed system provides better security and has a lower computational complexity than other methods. Furthermore, the proposed system is resistant to known attacks such as brute force and statistical attacks.

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.

Color image encryption scheme combining a 2D hyperchaotic Sin–Henon system and the division algorithm

As an important transmission medium, color images can provide more information, but in the process of image encryption, few algorithms fully consider the relationship between three color planes. To achieve a more secure and effective color image encryption effect, we propose a novel scheme combining a 2D hyperchaotic Sin–Henon system (2D-SH) and the division algorithm. 2D-SH is designed based on Sin mapping and Henon mapping, which has a broader chaotic range, better ergodicity, and more complicated chaotic behavior. The division algorithm is applied to the chaotic sequences produced by 2D-SH to generate a position matrix and two pseudo-random matrices for cross-plane scrambling and diffusion. The main encryption process involves three steps. Firstly, a color plaintext image is dimensionally reduced and preprocessed into a 2D pixel matrix to improve the efficiency of scrambling and diffusion. Secondly, the position matrix is used to achieve cross-plane scrambling. Finally, the pseudo-random matrices and the position matrix are used to realize synchronous diffusion and scrambling. The algorithm is simple in structure and can complete the encryption with only one round of the process. Simulation experiments and security analyses demonstrate that the proposed algorithm can not only encrypt images securely and fast, but also successfully pass various tests, demonstrating robustness and effectiveness. In addition, SH-CIEA outperforms some latest algorithms in terms of variance, entropy, and other aspects. The calculation time is nearly 0.61 s, showing its efficiency for practical applications.

Harris Hawk optimization driven adaptive image encryption integrating Hilbert vibrational decomposition and chaos

Image encryption is a technique used to protect the confidentiality of digital images. Existing encryption algorithms use chaotic maps for generating random sequences. These sequences purely depend on the fixed initial parameters, which are not adaptive to different input images, thereby limiting their ability to produce the best-possible encrypted image. This paper introduces a new Harris Hawk optimization (HHO) based adaptive image encryption algorithm that integrates Hilbert vibrational decomposition (HVD), and multiple chaotic maps. The new fitness function is specifically designed to optimize the security and robustness of the encrypted image, considering statistical and differential attack parameters (NPCR, UACI, Entropy, and correlation coefficient values). HHO is used to optimize the initial parameters of chaotic maps (Henon map, Duffing map, Lorenz equation) subject to variations in the input image. In the confusion stage, the input image is decomposed into four components of same dimension but decreasing energy using HVD. Subsequently, the block based pixel scrambling is performed on alternate components using the Henon map and Duffing map. In the diffusion stage, the image from the confusion stage undergoes a first level diffusion by bitwise XOR operation with a random image generated from the Lorenz equation. Further, second level of diffusion is achieved with a complex operation generated image from the input image, enhancing its adaptability. Finally, Arnold Cat map having number of iterations determined by the input image is used for final pixel permutation to produces the encrypted image. The optimized initial parameters and input image dependent confusion and diffusion operations enable the encryption system to adapt to changes in the input image, thereby enhancing its resistance against known plain text and known cipher text attacks. Moreover, the integration of HVD with multiple chaotic maps makes the scheme more complex to decrypt with plain text attacks. The performance of proposed algorithm is evaluated on five standard test images in terms of security and quality measures. Experimental results exhibit statistical and differential attack parameters close to ideal values (with Max. Entropy≈7.9996, Min. CC≈ 10−5, Max. NPCR≈99.64, Max. UACI≈33.62). The use of multiple chaotic maps at different stages makes the key space larger. Robustness analysis demonstrates the algorithm's capability in withstanding noise and image enhancement attacks. The comparison with state of the arts metaheuristic based and classical encryption algorithms highlights the superior performance of proposed HHO driven algorithm. The significant improvement in security parameters and overall fitness compared to fixed initial parameters is achieved by optimizing the encryption process.

A dual image encryption method based on improved Henon mapping and improved Logistic mapping

A dual image encryption method based on improved Henon mapping and improved Logistic mapping

An encrypted hiding scheme for 3D objects based on CGH and Henon mapping

A method is proposed to enhance the security of three-dimensional (3D) objects through computer-generated hologram (CGH) encryption and hiding. The process begins by encoding the 3D object using an iterative angular-spectrum layer-oriented method to create an optimized phase-only CGH. Next, the encrypted image is produced by modulating the phase-only CGH with a chaotic random phase mask (CRPM) generated through Henon mapping. Subsequently, a combination of discrete wavelet transform (DWT) and singular value decomposition (SVD) is utilized to embed the encrypted data into a visually secure image, ensuring the encryption and concealment of 3D objects. During decryption, the accurate decryption procedure and keys must be applied to achieve the final reconstruction. The utilization of CGH in conjunction with CRPM effectively enhances the security of 3D objects, while the integration of DWT and SVD ensures the visual security properties of the encrypted data, providing a dual layer of protection for 3D objects. Experimental simulation results demonstrate that this approach achieves high-security encryption and concealment of 3D objects, ensuring high-quality decryption of 3D objects during the reconstruction process.

Colour Image Encryption and Decryption using Arnold’s Cat Map and Henon Map

Image encryption plays a crucial role in securing sensitive visual information during transmission and storage. Throughout the encryption and decryption phases of images, the utilized ciphers exhibit substandard quality, resulting in the persistence of the original image. Consequently, the issues at hand stem from a deficiency in the quality of cipher image, thereby compromising the confidentiality level to an unsafe extent. This research explores the application of chaotic maps, specifically the Arnold Cat Map and Henon Map for the encryption and decryption of digital colour images. The encryption process involves applying the Arnold Cat Map and Henon Map to permute and diffuse pixel values, enhancing the confusion and diffusion properties essential for robust encryption. The study provides insights into the decryption efficiency and the ability to recover the original image from the ciphered version. This research contributes to the body of knowledge in colour image encryption techniques and offers a novel approach leveraging chaotic maps. The findings emphasize the importance of selecting suitable chaotic maps and their parameters to achieve a balance between security and image quality.

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.

Optimized and secure digital image watermarking technique using Henon mapping in redundant domain

Optimized and secure digital image watermarking technique using Henon mapping in redundant domain

Fast and Secure Image Encryption System Using New Lightweight Encryption Algorithm

The rapid evolution of network technologies, where computer vision and the Internet seamlessly merge, poses significant challenges in safeguarding end-user data. To address the growing need for secure data in smart environments, lightweight and efficient security solutions are in high demand. Notably, the Trivium, a well-known encrypt stream cipher (eSTREAM) project, has been the target of several attacks. This paper proposes an innovative approach for fast and highly secured image encryption using byte scrambling and a modified version of the Trivium algorithm. The Henon map is utilized to generate random numbers for permutation, reducing time and increasing security. Performance is measured on 100 colour images with different several tests. The results present a fast and robust security system for the transmission process. It is more efficient than the traditional Trivium method. The encrypted-decryption time is reduced by 1:24 times, making it a quick security system for surgical telepresence and multimedia visuals.

An efficient image encryption algorithm using a discrete memory-based logistic map with deep neural network

In the last few years, multimedia technology has made tremendous strides. These days, the Web is frequently used to transfer multimedia content, including audio, video, and photos. However, the Internet is a very vulnerable medium with many security holes. To ensure that multimedia content carried across unprotected channels, like the Internet, is secure and private, several encryption techniques have been proposed. New encryption strategies must be developed because multimedia data streams cannot be encrypted using traditional methods. Therefore, the main goal of the recommended system is to present an analytical research approach for introducing a sophisticated framework wherein the suggested encryption technologies' efficacy is increased through the use of deep neural networks (DNNs). The robustness of the DNN principle is coupled with a discrete memristor-based logistic chaotic map notion for enhanced security performance. In this paper, three distinct encryption algorithms—Arnie cat with an artificial neural network (ANN), Henon map with an ANN, and logistic map with a DNN—are compared for security and performance with the suggested algorithm. Correlation coefficients, information entropy, number of pixels changing rate (NPCR), encryption quality, and encryption duration are the cryptographic analysis parameters examined here. The results show that the recommended implementation enhances security performance without degrading image quality. The proposed algorithm achieves 35.9% of UACI, 99.95% of NPCR, and 7.997231 of entropy.

Using GAN-Based Encryption to Secure Digital Images With Reconstruction Through Customized Super Resolution Network

Unlike traditional encryption methods, Generative Adversarial Network (GAN)-based methods possess a high level of security for digital images. Many existing simple encryption methods may be less secure than expected and have high storage costs. This paper proposes a GAN-based encryption method to secure digital images, solving these problems. First, a random sequence generator using a GAN with cross-coupled logistics and a Henon map is generated to encrypt an image. Next, the encrypted image is downsampled into one-fourth of the original size and sent to the receiver. Finally, image reconstruction uses a Customized Super Resolution Network (CSRNet) rather than decompressing the image at the receiver side. Our extensive experimental results demonstrate that the proposed method achieves NPCR, UACI, entropy, PSNR and SSIM up to 0.99604, 0.33460, 7.9993, 37.0462 dB and 0.94561, respectively. Further, our encryption method achieves up to 75% faster than the recent methods when evaluated on two standard datasets. Therefore, the proposed GAN-Based solution can possess a high level of security and save sufficient storage space for any practical application.

Few-detail image encryption algorithm based on diffusion and confusion using Henon and Baker chaotic maps

Few-detail image encryption algorithm based on diffusion and confusion using Henon and Baker chaotic maps

A forensic framework to improve digital image evidence administration in IIoT✰

The extensive growth of Industrial Internet of Things (IIoT) has prompted cyber attackers to commence a variety of attacks which need to be identified to maintain the security of industrial data and services. Digital forensics is an extravagant need to detect cyber attacks and to identify cybercriminals. While conducting criminal investigation using digital forensics, there is high probability of leakage of collected digital evidence. Hence, the need for a secure and lightweight cryptosystem arises to protect it from cyber-attacks. In the present paper, authors aim to design a novel forensic framework for digital evidence administration using advanced encryption and preservation mechanisms. Authors focus to encrypt and preserve only digital image evidence but can be deployed on other types of multimedia data like video frames. Three types of Chaos-map algorithms namely 4D hyperchaotic map, 2D Arnold Cat map (ACM) and Henon Map have been utilized to encrypty and decrypt digital image evidence which enable high sensitivity and dependency on initial conditions, quasi-randomness, and ergodicity to digital content. The proposed approaches have been analyzed on different groups of images of different size and validated using various security parameters such as unified average changing intensity (UACI), correlation coefficient, and the number of pixels changing rate (NPCR). Image transformation and compression has been performed after encryption process using Fast Fourier Transformation (FFT). The proposed work has been analyzed using histogram and auto-correlation. Experimentations have provided the values of the correlation coefficient of plain images near 1 and the value of adjacent cipher images near zero which show a strong correlation. The evaluated results for UACI are more than 33 % for every considered images. The value for NPCR should be near 100 % and here the calculated results for each image are above 99 %. The complexity of the proposed encryption algorithm is O(n) due to key generation using a cryptographically secure pseudo-random number generator (CSPRNG). The compressed and transformed image evidence have been stored into decentralized blockchain to ensure the integrity and confidentiality. Decentralized blockchain has been used as a reliable and promising solution to preserve digital evidence due to its distinct features like secure peer to peer communication, improved trust and transparency among participants, integrity, confidentiality, immutability, without risk of single point-of-failure. The proposed digital forensic model is able to prevent various threats and security challenges which can contaminate or tamper off digital pieces of evidence and assures improved digital evidence administration and defensibility. In the proposed scheme, the encryption process takes only 2–3 s to perform the encryption of each size of image.

Cryptanalysis of an image encryption scheme based on two-point diffusion strategy and Henon map

In recent year, an image encryption scheme was proposed based on Henon map and two-point diffusion strategy. Two-point diffusion method improved the conventional permutation–diffusion architecture by allowing two cryptographic primitives, i.e. permutation and diffusion intermingling with each other in every single round. In this paper, we show the dynamical degradation of digital Henon map using state-mapping network. By comparing to the exhaustive key search, applying algebraic cryptanalysis and chosen plaintext attack require lower time complexity of computation. The recovery of equivalent keys also reduces the possible numbers of secret keys. The keystream recovery process has been verified using simulations. We also show that the two-point diffusion strategy does not improve the efficiency of the image encryption scheme and some improvement suggestions using parallel computing are given. As a nutshell, extra care needs to be taken when selecting chaotic map and assessing the security of future proposals based on the two-point diffusion strategy schemes.

Design of S-box multi-objective optimization algorithm based on combined chaotic system

S-box is the only nonlinear cryptographic component that determines the security of the block cipher. The higher the security of the S-box, the higher the security of the block cipher. Therefore, this paper proposes an S-box multi-objective optimization algorithm based on the combined chaotic system. Firstly, designing an integrated chaotic system based on a fractional index and its dynamic behavior is studied; it shows incredibly high-performance stability and chaotic parameter range coverage in the entire parameter space. A novel chaotic S-box construction algorithm is proposed based on the combined chaotic system. It introduces a linear congruential pseudo-random number generator to extend the sequence period and scramble the chaotic S-box through Henon mapping to improve the nonlinearity of the s-box. Finally, introducing a teaching and learning multi-objective optimization model and the performance evaluation criteria of the S-box are incorporated into the design of the objective function; this design enables the resulting S-box to perform well under multiple performance indicators, and then the approximate optimal S-box in the population is obtained. Through the performance test of the approximate optimal S-box, the comparative analysis shows that the S-box has good cryptographic performance, can resist linear analysis and differential analysis, and has a good application prospect in lightweight cipher.