Image Encryption Method Research Articles

Thumbnail-Preserving Encryption Based on Binary–Decimal Hybrid and a Generalized Coupled Logistic Map

Traditional image encryption methods typically make a trade-off between privacy protection and visual usability. To address this issue, a novel thumbnail-preserving encryption scheme is proposed based on a hybrid of decimal and binary pixel values in three pixel groups, utilizing the excellent dynamic characteristics of a generalized coupled logistic map. Theoretically, it is proved that the core algorithm of this scheme is sum-preserving. Experimentally, it is demonstrated that this scheme not only excels in efficiency and resistance to attacks, effectively safeguarding image privacy, but also retains high-quality thumbnails after encryption, achieving both objectives of image privacy protection and visual usability.

Fast Color Image Encryption Algorithm Based on DNA Coding and Multi-Chaotic Systems

At present, there is a growing emphasis on safeguarding image data, yet conventional encryption methods are full of numerous limitations. In order to tackle the limitations of conventional color image encryption methodologies, such as inefficiency and insufficient security, this paper designs an expedited encryption method for color images that uses DNA coding in conjunction with multiple chaotic systems. The encryption algorithm proposed in this paper is based on three-dimensional permutation, global scrambling, one-dimensional diffusion and DNA coding. First of all, the encryption algorithm uses three-dimensional permutation algorithms to scramble the image, which disrupts the high correlation among the image pixels. Second, the RSA algorithm and the SHA-256 hashing algorithm are utilized to derive the starting value necessary for the chaotic system to produce the key. Third, the image is encrypted by using global scrambling and one-dimensional diffusion. Finally, DNA coding rules are used to perform DNA computing. The experimental results indicate that the encryption scheme exhibits a relatively weak inter-pixel correlation, uniform histogram distribution, and an information entropy value approaching eight. This shows that the proposed algorithm is able to protect the image safely and efficiently.

An Image Encryption Method Based on a High-performance and Efficient Block Cipher

An Image Encryption Method Based on a High-performance and Efficient Block Cipher

A comprehensive review of quantum image encryption methods: design characteristics, cryptographic properties, and AI integration

A comprehensive review of quantum image encryption methods: design characteristics, cryptographic properties, and AI integration

Research on Image Encryption Method based on the Chaotic Iteration of a Ternary Nonlinear Function

Objective: Considering that some image encryption algorithms have the disadvantages of complex structure and high computational cost, and there are not many commonly used chaotic systems, which are easy to crack by attacks, to solve these problems, this paper proposes an image encryption algorithm based on three-dimensional nonlinear functions to solve these problems. Methods: The algorithm mainly combines the sinusoidal chaotic map with the ternary nonlinear function system to encrypt the image. Firstly, multiple ternary nonlinear function chaotic systems are designed. Then, the function iteration system is changed to invoke the computation of a specific expression under a random number; it is a chaotic sequence generated according to a chaotic mapping such as sine, and then the value of this chaotic sequence is used to select a ternary nonlinear function for iteration to obtain a chaotic sequence. Finally, the chaotic sequence performs the XOR and scrambling operations on the grey image Results: The algorithm has a simple structure, a better encryption effect, and more incredible difficulty deciphering. Moreover, through the phase diagram and bifurcation diagram, it can be seen that the system has good chaotic characteristics Conclusion: The method in this paper is novel; this method is a random variable order composite operation, which can not only be applied to image encryption but also can be used for fractal map generation and so on, and in some other chaotic fields will have a wide range of applications. It has essential research value.

Security of End-to-End medical images encryption system using trained deep learning encryption and decryption network

The Internet of Medical Things (IoMT) links medical devices and wearable, enhancing healthcare. To secure sensitive patient data over the IoMT, encryption is vital to retain confidentiality, prevent tampering, ensure authenticity, and secure data transfer. The intricate neural network architecture of deep learning models adds a layer of complexity and non-linearity to the encryption process, rendering it highly resistant to plaintext attacks. Specifically, the Cycle_GAN network is used as the leading learning network. This work suggests deep learning-based encryption for medical images using Cycle_GAN, a Generative Adversarial Network. Cycle_GAN changes images without paired training data that improves quality and feature preservation. Unlike conventional image-to-image translation techniques, Cycle_GAN doesn’t require a dataset with corresponding input–output pairs. Traditional methods typically needs paired data to learn the mapping between input and output images. Paired data can be challenging to obtain, specifically in medical imaging where gathering and annotating data can be time-consuming, laborious and expensive. The use of Cycle_GAN overwhelms this constraint by using unpaired data, where the input and output images are not explicitly paired. This method ensures confidentiality, authenticity, and secure transfer. Cycle_GAN consists of two major components: a generator used to modify the images, and a discriminator used to distinguish between real and fake images. Further, the Binary-Cross Entropy loss function is employed to train the network for precise predictions. The experiments are carried out on skin cancer datasets. The results demonstrate high-level efficient, systematic and coherent encryption as compared with other modernized medical image encryption methods. The proposed technique offers several benefits, including efficient encryption and decryption and robustness against unauthorized access.

A novel image encryption method based on the cycle replacement

For the bit-level image encryption algorithms, pixel values and positions can be changed simultaneously. The operation can enhance the security of image encryption but will require the complicated calculations. Therefore, high security and suitable computation for a new algorithm are needed to be considered. In this paper, a novel image encryption algorithm, which combines the bit-level encryption and the pixel-level encryption methods, is proposed based on the cycle replacement. Firstly, a new 2-dimensional (2D) map with a hyperbolic cosine function (2D-Cosh map) is introduced, which has rich and complex dynamics. Based on the chaotic characteristic of the map, an image encryption algorithm is introduced via the substitution of bit of pixels which can scramble the pixels, and change the image pixel positions effectively. Numerical simulation and security analysis are used to demonstrate the effectiveness and feasibility of the algorithm. From which we can see that the correlation coefficients are almost 0, average entropy = 7.9973, average NPCR = 99.6104%, and average UACI = 33.4664%. It is clear that the algorithm is resistant to differential attacks, interference attacks, and can reduce the correlation of adjacent pixels of the encrypted image greatly. Meanwhile, the algorithm has no limit for the size of a color image in the process of the encryption.

Optical phase image encryption using stokes parameters and singular value decomposition

Abstract In this paper, we propose an optical asymmetric phase image encryption method in which the vectorial light field is used to encode the data. In transverse plane, the vectorial light field has spatially varying polarization distributions where we are allowed to have a greater number of degrees of freedom. In this scheme, the input image is first phase encoded and then modulated by a phase encrypting key, synthesized from the speckles obtained by the scattering of Hermite–Gaussian beams. The modulated image is further processed using fractional Fourier transform with a specific order (α). A pixel scrambling operator is utilized to increase the randomness to further enhance the security and singular value decomposition approach is employed to add the nonlinearity in the encryption process. Now, the stokes parameters, i.e. S 1 and S 2 are calculated using the light intensities correspond to different polarizations. S 1 is used as the encrypted image for transmission and S 2 is reserved as one of the private decryption keys. The robustness of the proposed technique is tested against various existing attacks, such as known plaintext attack, chosen plaintext attack, and contamination attacks. Numerically simulated results validate the effectiveness and efficiency of the proposed method.

An image encryption scheme based on an improved memristive neuron chaotic system

With fast-developing Internet and communication, the security transmission of image in network has become a research highlight. So far, researchers have designed a lot of image encryption methods based on chaotic models, some of them are not secure enough. To enhance security of image transmission on the network, in this paper, an image encryption method is developed from a 3D memeristive FitzHugh-Nagumo (FHN) neuron. First, a 3D memeristive FHN model is obtained by connecting a memeristor into a 2D FHN model, and dynamics for 3D FHN model are estimated by applying phase diagrams, bifurcation and Lyapunov exponent. Then, an image encryption algorithm is proposed by using this 3D model. Finally, security of encryption algorithm is estimated. Simulation results confirm the effectiveness of encryption scheme.

A novel color image encryption method based on new three-dimensional chaotic mapping and DNA coding

A novel color image encryption method based on new three-dimensional chaotic mapping and DNA coding

A novel image encryption method based on improved two-dimensional logistic mapping and DNA computing

In the digital era, the significance of cryptographic algorithms has grown significantly within the realm of cybersecurity. This research presents an innovative approach to image encryption that eliminates the security limitations of the conventional one-dimensional logistic mapping. This approach relies on an enhanced two-dimensional logistic-fraction hybrid chaotic mapping (2D-LFHCM) and deoxyribonucleic acid (DNA) computing. Initially, the improved 2D-LFHCM is utilized to effectively scramble the image by incorporating chaotic sequences. Then, two novel algebraic DNA computing rules are introduced to enhance diffusion encryption. Experimental findings show that this approach offers superior security performance, even with renowned attacks.

Maze based image encryption method constructed by random number generation

Due to the large size of image files and the high correlation between the numerical values of the pixels, various improved algorithms have been used for image encryption in recent years. In most cases improvement is obtained by taking into account the characteristics of chaotic and random processes in encryption algorithms. In this study, an algorithm is proposed that encrypts images based on a maze created by keys consisting of random numbers generated with Feigembaum’s quadratic function. For the generation of the maze, deep first search (DFS) algorithm has been used. During the generation with this algorithm, numbers representing the walking paths and as well as the length of the used stack are included in the encryption process. Algorithm security verification was carried out according to key space and differential analysis, statistical analysis such as entropy estimation, and analysis of correlation between the histogram and neighboring pixels of the image.

A novel plaintext-related image encryption and compression method based on a new coupled map lattices model

In this paper, we propose a new Sine-Logistic Map Coupled Map Lattices (SLMCML) model, which exhibits enhanced chaotic characteristics and more suitable for image encryption compared with the classical coupled map lattices. Based on the SLMCML system, we propose an image encryption and compression method. To improve the plaintext sensitivity of image cryptosystem, we propose a novel plaintext-related internal keys generation method, which can obviously improve the plaintext sensitivity of initial values of SLMCML system, thus improve the plaintext sensitivity of whole process of compression and encryption. Our proposed image encryption scheme contains several steps. Initially, the discrete wavelet transform (DWT) is utilized to convert original image into coefficient matrix. Then a plaintext relation method is constructed, which generate internal keys as initial values of SLMCML system. Next the coefficient matrix is permutated by permutation sequences generated by SLMCML system to cyclic shift for making the energy evenly distributed. Next the coefficient matrix is done sparse processing. The compressed sensing is employed to compress coefficient matrix. Subsequently, the compressive image is permutated with spiral traversal and twice zigzag transform. Finally, the permutated image is diffused with column diffusion to generate cipher image. Through some common security analyses, our proposed image encryption scheme has good security performance and excellent image recovery quality.

Achieving Image Encryption Quantum Dot-Functionalized Encryption Camera with Designed Films.

The risk of information leaks increases as images become a crucial medium for information sharing. There is a great need to further develop the versatility of image encryption technology to protect confidential and sensitive information. Herein, using high spatial redundancy (strong correlation of neighboring pixels) of the image and the in situ encryption function of a quantum dot functionalized encryption camera, in situ image encryption is achieved by designing quantum dot films (size, color, and full width at half maximum) to modify the correlation and reduce spatial redundancy of the captured image during encryption processing. The correlation coefficients of simulated encrypted image closely apporach to 0. High-quality decrypted images are achieved with a PSNR of more than 35dB by a convolutional neural network-based algorithm that meets the resolution requirements of human visual perception. Compared with the traditional image encryption algorithms, chaotic image encryption algorithms and neural network-based encryption algorithms described previously, it provides a universal, efficient and effective in situ image encryption method.

Developing a secure image encryption technique using a novel S-box constructed through real-coded genetic algorithm’s crossover and mutation operators

The objective of this study is to craft a novel S-Box tailored to stringent security standards, achieved through iterative application of crossover and mutation operators inherent to real-coded genetic algorithms, ensuring robust image encryption. The designed S-Box is rigorously evaluated across multiple criteria, demonstrating its superiority over comparable S-Box designs found in existing literature. Furthermore, a secure image encryption method based on the designed S-Boxes devised and also including a 2D hyperchaotic Styblinski–Tang map. Thorough security assessments, encompassing statistical analysis and resilience testing against diverse attacks and noise, it is validated the encryption technique’s efficiency and applicability across varied scenarios.

A novel color image encryption method using Fibonacci transformation and chaotic systems

INTRODUCTION: With the rapid increase in network information data, the protection of image data has become a challenging task, where image encryption technology can play an important role. This paper studies color image encryption algorithms and proposes a novel method for color image encryption to enhance the security and effectiveness of image encryption.OBJECTIVES: The purpose of this study is to effectively integrate different channel information of color images, thereby improving the effect of pixel decomposition based image encryption algorithm. Different indicators are used to analyze the effect of image encryption, and it is also compared with existing image encryption algorithms.METHODS: Initially, through pixel decomposition, the pixel values of the R, G, B channels of the color image, each with a depth of 8 bits, are decomposed into two integers between 0-15 and combined into a new data matrix. Then, multiple rounds of scrambling are performed on the transformed matrix. Next, the Fibonacci transformation matrix is applied to the scanned matrix to further change the values of its elements. Finally, XOR diffusion operation is carried out to obtain the encrypted image.RESULTS: Experimental results show that the proposed method achieves relatively good results in multiple image encryption indicator tests. The algorithm not only inherits the advantages of existing image encryption but also effectively integrates the information of each channel of the color image, providing better security.CONCLUSION: This study further proves the effectiveness of image encryption algorithms based on pixel decomposition and provides a new idea for better color image encryption algorithms, which is expected to be applied to other issues such as information hiding and data protection.

Novel hyperchaotic image encryption method using machine learning-RBF

Novel hyperchaotic image encryption method using machine learning-RBF

Image encryption algorithm based on a memcapacitor‐based hyperchaotic system and DNA coding

AbstractIn today's digitally connected world, the protection of privacy and data security in open communication media (OCM) is paramount. As digital devices become more widespread and increase in global connectivity, the significance of image encryption has reached unprecedented levels. Traditional encryption techniques often fall short when applied to images due to their unique properties such as high correlation and large data quantities. To address these challenges, this paper presents a novel image encryption method that integrates principles from deoxyribonucleic acid (DNA) rules, the logistic map, and a hyperchaotic model with memcapacitors. The intricate and unpredictable nature of the memcapacitor‐based hyperchaotic system, coupled with deficiencies in current image encryption algorithms, serves as a catalyst for the development of this new algorithm. The proposed encryption strategy leverages the encoding properties of DNA and the complex dynamics of hyperchaotic systems to achieve enhanced image encryption. Through simulations and evaluations using reference images, the effectiveness of the method is demonstrated. It surpasses current techniques in terms of statistical robustness, resistance to brute‐force attacks, and protection against differential attacks. The research concludes that combining DNA principles, logistic maps, and memcapacitor‐based hyperchaotic systems significantly improves image encryption. This approach enhances data security for image transmission in open communication channels, addressing the limitations of traditional encryption techniques. As digital connectivity expands globally, the demand for robust image encryption is expected to increase, making this research pivotal in establishing standards for future advancements in image encryption algorithms.

New method of colour image encryption using triple chaotic maps

AbstractA new image encryption algorithm based on the triple chaotic maps is proposed to deal with the issues of inadequate security and low encryption efficiency. Coloured images consist of three linked channels used in the scheme. This method uses different keys to break the correlations between adjacent pixels in each channel. The triple chaotic maps are Lorenz, 2D‐Logistic, and Henon. First, the plain image is split into RGB channels to encrypt each channel separately. Second, the triple chaotic maps generate two groups of keys. The first group of keys performs a pixel permutation, resulting in scrambled channels used as input for the following step. Finally, the second group of keys is used to diffuse the scrambled channels independently, resulting in diffused channels, which are then merged to obtain a cipher image. The triple chaotic maps of different orders generate the cipher image with great unpredictability and security. The security is evaluated using various measures. The results demonstrated a high level of security attained by successfully encrypting coloured images. Recent encryption algorithms are compared in terms of entropy, correlation coefficients, and attack robustness. The proposed method provided outstanding security and outperformed existing image encryption algorithms.

Hyperchaotic color image encryption scheme based on simultaneous color channel confusion-diffusion operations

Shortcomings have been identified in current color image encryption methods. Firstly, these methods encrypt each color channel separately, resulting in a time-consuming process and independent encrypted channels, which can make hacking easier. Secondly, the use of XOR operations between image pixel values and code values during encryption can be vulnerable. To address these issues, a novel algorithm is introduced that incorporates a new XOR operation and simultaneous encryption of color channels. This approach creates interdependence between the encrypted channels, reduces encryption time, and enhances security by introducing a more complex XOR operation. The proposed method employs a substitution technique that involves XOR operations between groups of pixels and codes, inspired by the principles of the fast Walsh-Hadamard transform algorithm. The encryption process involves several key phases that enhance the security and efficiency of the system. In the initial phase, line processing involves mixing lines from different channels and application of chaotic substitution permutation operations. Subsequently, a similar operation is applied to columns, and finally, the channels are divided into overlapping squared sub-blocks, with a newly XOR proposed chaos-based confusion operation simultaneously applied to the three-channel sub-blocks. These phases are designed to ensure interdependence between color channels and reduce encryption time, resulting in a more robust encryption method. With this method, the RGB cipher channels become mutually dependent, rendering decryption of one channel impossible without the others. The approach has been evaluated using appropriate metrics and found to be robust, efficient, and resistant to various attacks, outperforming recently published methods. It is suitable for modern image encryption applications, including those related to the Internet of Medical Things (IoMT).