Image Encryption Method Research Articles

A Color Image Encryption Method Based on Dynamic Selection Chaotic System and Singular Value Decomposition

As the basis for guiding business process decisions, flowcharts contain sensitive information pertaining to process-related concepts. Therefore, it is necessary to encrypt them to protect the privacy or security of stakeholders. Using the principles of image singular value decomposition, chaotic system randomness, and neural network camouflage, a business flow chart encryption method based on dynamic selection chaotic system and singular value decomposition is proposed. Specifically, a dynamic selected chaotic system is constructed based on the nonlinear combination of one-dimensional chaotic system Logistics and Sine, and its randomness is verified. Next, using the neural network, the process image is merged into a gray matrix. The double-bit unitary matrix scrambling based on singular value decomposition is then proposed. Subsequently, using the dynamic selected chaotic system, a new sub-division diffusion method is proposed, which combines, diffuses, and performs weighted superposition to generate a matrix after diffusion and compression. Finally, the asymmetric encryption method encrypts the color image and reduces its dimensionality into a single grayscale ciphertext, and the decryption process is not the reverse of the encryption process. Simulation results and performance analysis show that the proposed image encryption scheme has good encryption performance.

Chaotic medical image encryption method using attention mechanism fusion ResNet model.

With the rapid advancement of artificial intelligence (AI) technology, the protection of patient medical image privacy and security has become a critical concern in current research on image privacy protection. However, traditional methods for encrypting medical images have faced criticism due to their limited flexibility and inadequate security. To overcome these limitations, this study proposes a novel chaotic medical image encryption method, called AT-ResNet-CM, which incorporates the attention mechanism fused with the ResNet model. The proposed method utilizes the ResNet model as the underlying network for constructing the encryption and decryption framework. The ResNet's residual structure and jump connections are employed to effectively extract profound information from medical images and expedite the model's convergence. To enhance security, the output of the ResNet model is encrypted using a logistic chaotic system, introducing randomness and complexity to the encryption process. Additionally, an attention mechanism is introduced to enhance the model's response to the region of interest within the medical image, thereby strengthening the security of the encrypted network. Experimental simulations and analyses were conducted to evaluate the performance of the proposed approach. The results demonstrate that the proposed method outperforms alternative models in terms of encryption effectiveness, as indicated by a horizontal correlation coefficient of 0.0021 and information entropy of 0.9887. Furthermore, the incorporation of the attention mechanism significantly improves the encryption performance, reducing the horizontal correlation coefficient to 0.0010 and increasing the information entropy to 0.9965. These findings validate the efficacy of the proposed method for medical image encryption tasks, as it offers enhanced security and flexibility compared to existing approaches. In conclusion, the AT-ResNet-CM method presents a promising solution to address the limitations of traditional encryption techniques in protecting patient medical images. By leveraging the attention mechanism fused with the ResNet model, the method achieves improved security and flexibility. The experimental results substantiate the superiority of the proposed method in terms of encryption effectiveness, horizontal correlation coefficient, and information entropy. The proposed method not only addresses the shortcomings of traditional methods but also provides a more robust and reliable approach for safeguarding patient medical image privacy and security.

A hybrid color image encryption method based on extended logistic map

A hybrid color image encryption method based on extended logistic map

A Privacy-Preserving JPEG Image Retrieval Scheme Using the Local Markov Feature and Bag-of-Words Model in Cloud Computing

The development of cloud computing attracts a great deal of image owners to upload their images to the cloud server to save the local storage. But privacy becomes a great concern to the owner. A forthright way is to encrypt the images before uploading, which, however, would obstruct the efficient usage of image, such as the Content-Based Image Retrieval (CBIR). In this paper, we propose a privacy-preserving JPEG image retrieval scheme. The image content is protected by a specially-designed image encryption method, which is compatible to JPEG compression and makes no expansion to the final JPEG files. Then, the encrypted JPEG files are uploaded to the cloud, and the cloud can directly extract the features from the encrypted JPEG files for searching similar images. Specifically, big-blocks are firstly assembled with adjacent 8×8 discrete cosine transform (DCT) coefficient blocks. Then, the big-blocks are permuted and the binary code of DCT coefficients are substituted, so as to disturb the content of image. After receiving the encrypted images, local Markov features are extracted from the encrypted big-blocks, and then the Bag-Of-Words (BOW) model is applied to construct a feature vector with these local features to represent the image, so as to provide the CBIR service to image owner. Experimental results and security analysis demonstrate the retrieval performance and security of our scheme.

Subject review: Image encryption techniques

Security is one of the core areas of study in recent days. Encryption of the image is widely known as an effective method for its secure transmission. The objective of any image encryption method is to obtain a top quality hidden image in order to keep information secret. This paper is a study of research authors in the field of image encryption with a research review to see how the field of image encryption has progressed and the best algorithms in their performance.

Data Class-Specific All-Optical Transformations and Encryption.

Diffractive optical networks provide rich opportunities for visual computing tasks since the spatial information of a scene can be directly accessed by a diffractive processor without requiring any digital pre-processing steps. Here we present data class-specific transformations all-optically performed between the input and output fields-of-view (FOVs) of a diffractive network. The visual information of the objects is encoded into the amplitude (A), phase (P), or intensity (I) of the optical field at the input, which is all-optically processed by a data class-specific diffractive network. At the output, an image sensor-array directly measures the transformed patterns, all-optically encrypted using the transformation matrices pre-assigned to different data classes, i.e., a separate matrix for each data class. The original input images can be recovered by applying the correct decryption key (the inverse transformation) corresponding to the matching data class, while applying any other key will lead to loss of information. The class-specificity of these all-optical diffractive transformations creates opportunities where different keys can be distributed to different users; each user can only decode the acquired images of only one data class, serving multiple users in an all-optically encrypted manner. We numerically demonstrated all-optical class-specific transformations covering A → A, I → I, and P → I transformations using various image datasets. We also experimentally validated the feasibility of this framework by fabricating class-specific I → I transformation diffractive networks and successfully tested them at different parts of the electromagnetic spectrum, i.e., 1550 nm and 0.75 mm wavelengths. Data class-specific all-optical transformations provide a fast and energy-efficient method for image and data encryption, enhancing data security and privacy. This article is protected by copyright. All rights reserved.

A novel method of digital image encryption using graph theory

A novel method of digital image encryption using graph theory

Encryption algorithm based on fractional order chaotic system combined with adaptive predefined time synchronization

An image encryption and decryption method of fractional order chaotic systems (FOCS) with predefined time synchronization is proposed in this article. Compared with the existing integer order chaotic systems (IOCS), fractional order chaotic systems has the advantage of increasing the complexity of the ciphertext. At the same time, by using the predefined synchronization time, the key space is expanded, the complexity of the key is increased, and the security of the algorithm is improved. To further improve the security of encryption and decryption process, this article uses a combination of DNA encoding, row/column cyclic shift and XOR diffusion, position scrambling and Arnold scrambling. The simulation tests of image encryption and decryption are carried out, and the effectiveness and advantages of the proposed encryption/decryption method are verified by histogram analysis, correlation analysis, entropy analysis, key sensitivity analysis and plaintext sensitivity analysis.

Multibiometric Images Encryption Method Based on Fast Fourier Transform and Hyperchaos

Biometric images are an important means of personal identity verification and identification and are related to personal privacy and property security. To address the problems of poor security and low image reconstruction quality in the encryption and transmission of multibiometric images, a multibiometric images encryption method based on Fast Fourier Transform (FFT) and hyperchaotic system is proposed. First, the FFT is used to transform the multibiometric images from spatial to frequency domain. Then, the initial values of the hyperchaotic Lorenz system are generated using a one-dimensional chaotic logistic system to generate the key stream. Combined with the recoding rules of matrix reconstruction and scrambling without repetition of using multimatrix, the multiple matrices of amplitude and phase in the transform domain are reconstructed to be multiple RGB three-channel color images by using the inverse fast Fourier transform. Then, we combine the two diffusion methods of additive mode and Galois domain diffusion on each color channel to perform confusion and diffusion. Finally, the multiple grayscale images are encrypted to become multiple color images. The experimental results demonstrate that the method can effectively defend against various attacks. In addition, it solves the problem of low reconstruction accuracy that exists in the field of multiple images security.

A novel method for image encryption using time signature-dependent s-boxes based on latin squares and the playfair system of cryptography

A novel method for image encryption using time signature-dependent s-boxes based on latin squares and the playfair system of cryptography

An efficient hybrid fuzzy image encryption models for the secured cloud accessing in portable robotics devices

Secure sharing of image data through different communication channels is a challenging research issue in digital networks. In such cases, cryptography algorithms are widely used to encrypt and decrypt the information reliably at both ends of source and target destinations. Various state-of-the-art image encryption algorithms are surveyed and investigated to assess the best image encryption. In this paper, image encryption is described with various fuzzy operation modes. It ensures secure image transmission over to the digital channels. Most reliable image encryption is the aim of the work, and it is achieved through developing a hybrid fuzzy-based framework that composites the techniques of image encryption methods and fuzzy operation modes. Proposed hybrid fuzzy-based models are highly recommended to maintain secure information on portable robotics devices, communication channels, and routing devices. These hybrid encrypted models provide the users' privacy to access the image data with reliable security mechanisms.

A new image encryption method using Bezier curve

A new image encryption method using Bezier curve

Reversible Data Hiding in Encrypted Image via Joint Encoding of Multiple MSB and Pixel Difference

Reversible data hiding in encrypted image (RDHEI) has become a research hotspot, which can effectively protect image content privacy. An RDHEI scheme based on the joint encoding of multiple MSBs (most significant bits) and pixel difference is proposed in this paper. A block-based image encryption method is adopted on the content owner side, which can securely protect the image contents while retaining the spatial correlation within each block. By the joint encoding strategy of multiple MSB and pixel difference, the redundancy within the bit plane is sufficiently compressed to accommodate more additional data; thus, a high embedding rate can be achieved. According to different kinds of available keys, image decryption and data extraction can be separably conducted on the receiver side. Experimental results show that our scheme can achieve a higher embedding rate than some state-of-the-art schemes.

Hybrid partial differential elliptical Rubik’s cube algorithm on image security analysis

Purpose Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks. Design/methodology/approach In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle. Findings To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission. Originality/value The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

An image cryptography method by highly error-prone DNA storage channel.

Introduction: Rapid development in synthetic technologies has boosted DNA as a potential medium for large-scale data storage. Meanwhile, how to implement data security in the DNA storage system is still an unsolved problem. Methods: In this article, we propose an image encryption method based on the modulation-based storage architecture. The key idea is to take advantage of the unpredictable modulation signals to encrypt images in highly error-prone DNA storage channels. Results and Discussion: Numerical results have demonstrated that our image encryption method is feasible and effective with excellent security against various attacks (statistical, differential, noise, and data loss). When compared with other methods such as the hybridization reactions of DNA molecules, the proposed method is more reliable and feasible for large-scale applications.

Image encryption algorithm based on the density and 6D logistic map

One of the most difficult issues in the history of communication technology is the transmission of secure images. On the internet, photos are used and shared by millions of individuals for both private and business reasons. Utilizing encryption methods to change the original image into an unintelligible or scrambled version is one way to achieve safe image transfer over the network. Cryptographic approaches based on chaotic logistic theory provide several new and promising options for developing secure Image encryption methods. The main aim of this paper is to build a secure system for encrypting gray and color images. The proposed system consists of two stages, the first stage is the encryption process, in which the keys are generated depending on the chaotic logistic with the image density to encrypt the gray and color images, and the second stage is the decryption, which is the opposite of the encryption process to obtain the original image. The proposed method has been tested on two standard gray and color images publicly available. The test results indicate to the highest value of peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel change rate (NPCR) are 7.7268, 50.2011 and 100, respectively. While the encryption and decryption speed up to 0.6319 and 0.5305 second respectively.

A Fast Hyperchaotic Image Encryption Scheme

In this paper, we propose a fast hyperchaotic image encryption scheme based on RSVM and step-by-step scrambling-diffusion. In this scheme, we firstly propose a new algorithm named ring shrinkage with variable modulo (RSVM), which can randomly scramble the elements in a one-dimensional array, which are composed of the row numbers or column numbers of the pixel matrix to be encrypted. Before encryption, we use RSVM algorithm to generate two random one-dimensional arrays of pixel matrix (i.e. row array [Formula: see text] and column array [Formula: see text]), and each element in the [Formula: see text] represents the row/column number in the pixel matrix. Then the rows/columns of the pixel matrix are scrambled-diffused step-by-step according to the row/column numbers in the [Formula: see text]. The initial control parameters of RSVM algorithm are controlled by SHA-256 of plaintext pixels, and RSVM algorithm controls the step-by-step scrambling-diffusion process of pixel matrix, rows and columns, so the small changes of plaintext pixels will lead to great differences in ciphertext images. In addition, the overall time complexity of the image encryption scheme is only [Formula: see text], which can greatly reduce the time cost. Finally, the experimental results and extensive security analysis prove the efficiency and feasibility of this image encryption method.

A K-SVD Based Compressive Sensing Method for Visual Chaotic Image Encryption

The visually secure image encryption scheme is an effective image encryption method, which embeds an encrypted image into a visual image to realize a secure and secret image transfer. This paper proposes a merging compression and encryption chaos image visual encryption scheme. First, a dictionary matrix D is constructed with the plain image by the K-SVD algorithm, which can encrypt the image while sparsing. Second, an improved Zeraoulia-Sprott chaotic map and logistic map are employed to generate three S-Boxes, which are used to complete scrambling, diffusion, and embedding operations. The secret keys of this scheme contain the initial value of the chaotic system and the dictionary matrix D, which significantly increases the key space, plain image correlation, and system security. Simulation shows the proposed image encryption scheme can resist most attacks and, compared with the existing scheme, the proposed scheme has a larger key space, higher plain image correlation, and better image restoration quality, improving image encryption processing efficiency and security.

A color image encryption scheme using customized map

ABSTRACT The paper presents a new method for encrypting color images using a customized globally coupled lattice (CGCL) map. The process involves generating an initial parameter for the map using an SHA-128 hash function, which is then used to encrypt the image. Two different scrambling algorithms are used to improve the randomness of the encrypted image, and the DNA encoding procedure is used to further encrypt the permuted image components. The proposed scheme is shown to be robust against noise and crop attacks and effectively eliminates adjacent pixel correlation. The schemes information entropy, key space, NPCR, and UACI values are all close to ideal. The time complexity of the scheme is O(12×N×M), and it has a computation time of 2.97s, making it efficient. Overall, the simulation and performance analysis suggest that the proposed scheme is highly secure and resistant to foreign attacks, making it a promising method for color image encryption.

HİPERKAOTİK HARİTA VE GENETİK OPERATÖRLERE DAYALI YENİ BİR GÖRÜNTÜ ŞİFRELEME YÖNTEMİ

This paper presents a novel and secure image encryption method. The plain image’s pixels are confused using the N-point crossover operation of genetic algorithms. Randomly paired rows and columns are determined by the two state variables of a six-dimensional hyperchaotic map. The number of crossover points, which are calculated by the two other state variables of the hyperchaotic map, differ from each other for each row or column pair. The crossover positions are specified according to the number of crossover points with the help of the last two state variables. The proposed algorithm generates the diffusion stage’s encryption key using the SHA-256 hash value of the plain image. Mutation and crossover operators are implemented using the 16-bit subblocks of the 256-bit hash value. The scrambled image’s pixels are altered with the generated encryption key and previously encrypted pixels. Keyspace and sensitivity, histogram, correlation, information entropy, differential, data loss, noise attack, and computational time analyzes are performed to test the safety and effectiveness of the encryption method. The experiments and simulation results show that the proposed encryption technique is highly secure and efficient since it can resist various attacks.