Correlation Of Adjacent Pixels Research Articles

Efficient color image encryption algorithm based on 2D coupled chaos and multi-objective optimized S-box

In order to ensure the security of the encryption result and increase the speed of the encryption algorithm as much as possible, this paper proposes an efficient color image encryption algorithm based on 2D Sine-Logistic-Gaussian coupled chaos(2D-SLG chaos) and multi-objective optimized S-box. Firstly, this paper designs a 2D-SLG chaos to balance the complexity and computational cost of chaotic behavior. Secondly, this paper uses multi-objective particle swarm optimization to optimize the initial S-box to obtain an S-box with higher and balanced performance to perform the substitution operation. Finally, this paper uses the layer blending method to enhance the mutual influence between layers and uses the idea of linear congruence to generate permutation sequences to perform row and column shift operations. Experimental results show that the proposed encryption algorithm has excellent performance in key space, statistical analysis, key sensitivity, adjacent pixel correlation, differential attack, select plaintext attack and other security tests, and has high robustness and fast encryption speed. Therefore, the algorithm can meet the requirements of reliability and efficiency while ensuring strong security.

A conservative chaotic system with coexisting chaotic-like attractors and its application in image encryption

Unlike dissipative systems, conservative systems do not have attractors and no attractor reconstruction occurs. Therefore, these systems are more suitable for application in image encryption. On the basis of above appoints, here we develop and propose a conservative system with infinite chaotic-like attractors. The conservative and chaotic characteristics and coexistence chaotic-like attractors are studied using Lyapunov exponents, Poincare maps, and numerical simulation. The results show that the coexistence of chaotic-like attractors has a more complex structure and dynamic behaviour than traditional ones. Additionally, the developed system is further used to design an encryption system for a digital image. Using the coexistence chaotic-like attractor sequence to scramble and diffuse the image can destroy the correlation of adjacent pixels and hide the information of all pixels. The feasibility and security of the encryption scheme are demonstrated through the analysis of key space, histogram, information entropy, key sensitivity and pixel correlation.

Plaintext-related image encryption scheme based on chaos and game of life

To protect the security of image information in the process of storage or transmission, we propose an efficient image encryption method using chaos and game of life (GoL). First, a plaintext-related image scrambling method based on chaos and GoL is proposed to reduce the adjacent pixel correlation of the plain image. In this method, double scrambling is performed on the original image: the first scrambling matrix is constructed by logistic map and the rules of GoL; the second scrambling matrix is generated based on two-dimensional (2D) logistic map and magic square. The original image is scrambled by the above-mentioned scrambling matrices, which can efficiently reduce the strong adjacent pixel correlation, thus enhancing the image scrambling effect. Next, the 4D hyperchaotic system and GoL are employed to diffuse the scrambled image and get the cipher image. Additionally, the average pixel value of the original image is used to generate the initial values of the logistic map and 2D logistic map in scrambling process. Therefore, our encryption scheme is very sensitive to the plain image and can effectively resist the chosen-plaintext attack and known-plaintext attack. Finally, the experimental results and performance analyses show that the proposed encryption algorithm has the advantages of large key space and good scrambling effect, and it can effectively resist various typical attacks, so it can effectively protect the security of the image information.

Hybrid Facial Chaotic-based Graphical Encryption Technique for Cloud Environment

Pictographic representations are everywhere in this digital world. IoT, Cloud, Fog, and 5G systems are becoming data transfer boosters for each user. In a real-world situation, secure data transmission is critical through open networks. Many conventional cryptosystems are inadequate for graphical data privacy in terms of computational overhead, latency, and more sensitive to the unknown attacks. In this paper, the secured and low-complex chaotic-based facial image cryptosystem has been developed for computer vision image data. The proposed crypto system utilizes the facial features, Lorentz chaotic maps for private keys production during the encoding process and the same is decrypted using the diffusion process. Facial depictions are merged with chaotic maps that are segmented and decrypted with mutual keys. The performance of the proposed hybrid cryptosystem is validated using the standard facial datasets and NCPR, UACI metrics are measured. Entropy and adjacent pixels correlation metrics also evaluated through proposed cryptosystems.

Remodeled chaotic compressive sensing scheme for secure and energy-efficient data forwarding in body-to-body network

The Wireless Body Sensor Networks (WBSN) play an essential role in remote monitoring for healthcare, sports, disaster relief, military, etc. As the network scalability is expanding, the number of nodes and links is also increasing, further enhancing the computational complexity of the network. WBSN grows as the body-to-body network, and the most significant challenges faced while developing a WBSN are energy consumption and security. Therefore, a Remodeled Chaotic Compressive Sensing (RCCS) network based on the principle of storing matrix generation parameters is proposed in this work. Also, remodeled chaotic sensitivity utilized in the proposed network provides secured data transmission. The measurement matrix measures the physiological data in two directions for achieving compression and encryption simultaneously. The resulting data is encrypted by the operation of the duty shift, which RCCS controls. The secret key used in this algorithm is more sensitive; more than 15 discomposures of the secret key are realized, and it gives 100% relative error. This method provides a better result in image encryption and significant improvement in the security of the network, i.e., the vertical, horizontal, and diagonal, the correlation of adjacent pixels is less than 0.04 pixels in various directions. The cipher image entropy with 256- gray level value is more than 7.98 pixels. The human Body expands by the network in the proposed scheme, and the nodes interact via wireless communication. This system simplifies the required distribution and decreases the data space simultaneously.

Image Processing Method Based on Chaotic Encryption and Wavelet Transform for Planar Design

This paper provides an in-depth study and analysis of image processing for graphic design through chaotic encryption combined with a wavelet transform algorithm. Firstly, the traditional Mallat algorithm is optimized; since the mean value of the transform coefficients generated after the wavelet transform of the image is used as the initial value of the chaotic system to iterate, when the image is modified, then the mean value of the wavelet coefficients will also change, and the final iteration comes out as two different sequences using the property that the chaotic system is extremely sensitive to the initial conditions, so the algorithm has a certain sensitivity to tampering and localization effect. The image of the encrypted graphic design is decrypted by the chaos decryption system, and the final image information of the graphic design is obtained. In terms of the security of the graphic design image itself, the complex dynamical properties of chaos are fully utilized to encrypt it, and the algorithm has a good encryption effect after statistical characteristic analysis, attack complexity, difference analysis, adjacent pixel correlation analysis, and key sensitivity analysis. The plaintext image is decomposed in odd-even sequence using the boosting algorithm to get the sequence with an even index and the sequence with an odd index; then, the diffusion algorithm is applied to the two sequences by the prediction and update algorithm, and this process is repeated many times to get the two ciphertext sequences after scrambling, merging these two sequences, and matrixing them to get the ciphertext image. Finally, the testing of the embedded planar designed image revolves around four aspects, namely, image processing, tamper sensitivity, robustness, and imperceptibility, to examine the designed planar designed image system. In the diffusion manipulation, the key matrix for diffusion is obtained using the threshold processing method of the Local Binary Pattern (LBP) algorithm for the matrices generated by the Logistic Chaos system, which improves the randomness of the algorithm. The experimental results verify the effectiveness and security of the algorithm.

Real-time RGB image encryption for IoT applications using enhanced sequences from chaotic maps

Four chaotic maps are used herein as case study to design an embedded cryptosystem based on a pseudo-random number generator (PRNG). The randomness of the sequences is enhanced by applying the mod 1023 function and verified by analyzing bifurcation diagrams, the maximum Lyapunov exponent, and performing NIST SP 800-22 and TestU01 statistical tests. The PRNG is applied in a simple algorithm for real-time RGB images encryption on a machine-to-machine (M2M) scheme, using message queuing telemetry transport (MQTT) protocol over WiFi network and through Internet. The cryptanalysis confirms that the proposed image encryption scheme is robust to resist most of the existing attacks, such as statistical histograms, entropy, key-space, correlation of adjacent pixels, and differential attacks. The implementation of the proposed cryptosystem is done using enhanced sequences from the Logistic 1D map, and it reaches a throughput of up to 47.44 Mbit/s using a personal computer with a 2.9 GHz clock, and 10.53 Mbit/s using a Raspberry Pi 4. As a result, our proposed embedded cryptosystem is suitable to increase the security in the transmission of RGB images in real-time through WiFi networks and Internet.

A Multi-Image Encryption Based on Sinusoidal Coding Frequency Multiplexing and Deep Learning.

Multi-image encryption technology is a vital branch of optical encryption technology. The traditional encryption method can only encrypt a small number of images, which greatly restricts its application in practice. In this paper, a new multi-image encryption method based on sinusoidal stripe coding frequency multiplexing and deep learning is proposed to realize the encryption of a greater number of images. In the process of encryption, several images are grouped, and each image in each group is first encoded with a random matrix and then modulated with a specific sinusoidal stripe; therefore, the dominant frequency of each group of images can be separated in the Fourier frequency domain. Each group is superimposed and scrambled to generate the final ciphertext. In the process of decryption, deep learning is used to improve the quality of decrypted image and the decryption speed. Specifically, the obtained ciphertext can be sent into the trained neural network and then the plaintext image can be reconstructed directly. Experimental analysis shows that when 32 images are encrypted, the CC of the decrypted result can reach more than 0.99. The efficiency of the proposed encryption method is proved in terms of histogram analysis, adjacent pixels correlation analysis, anti-noise attack analysis and resistance to occlusion attacks analysis. The encryption method has the advantages of large amount of information, good robustness and fast decryption speed.

Image encryption scheme based on alternate quantum walks and discrete cosine transform.

As an important information medium, the digital image exists widely on the Internet. Quantum walks have the property of encrypting information. For the eneryption problem of optical digital images, an encryption scheme based on discrete cosine transform (DCT) and alternate quantum walks (AQW) is proposed in this paper. First, we use AQW and XOR operation to preprocess images in the spatial domain. Then, AQW are used to generate two random phase masks which can operate the preprocessed image and the DCT image, respectively. Finally, the encrypted image is obtained by using discrete cosine inverse exchange. The control parameters of AQW can replace the random phase mask as the key in the encryption and decryption process, so it is convenient for key management and transmission. The experimental simulation carried out the analysis of the image pixel histogram, the correlation of adjacent pixels, the robustness against noise and the sensitivity of secret keys, the results show that the image encryption method has strong security.

Visual Encryption Using Block based Scrambling Followed by Affine Encryption Technique

This article reports the Block based cipher concept followed by the affine cipher technique. The Image considered was grouped into squared (16, 32 and 64) pixel blocks then each column was shifted by specific values. These values were randomly generated prime numbers and worked as the key for scrambling. These images were investigated for their quality of scrambling using histogram and adjacent pixel correlation. The adjacent pixel correlations for 16, 32 and 64 pixel-based ciphered images were found as 0.7907, 0.7292, and 0.4783 respectively. The analysis gave the information that the level of scrambling was not satisfactory, therefore; the affine cipher technique was applied to each of the images. These images were converted into the matrix format and each element was transformed using the affine cipher. This transformed matrix is again converted inform from the image to visualize. The Histogram and adjacent pixel correction for these images were much improved.

Analytic Study of a Novel Color Image Encryption Method Based on the Chaos System and Color Codes

Due to the growing of the use of Internet and communication media, image encryption is rapidly increased. Image sharing through unsafe open channels is vulnerable for attacking and stealing. For protecting the images from attacks, encryption techniques are required. Recently, new and efficient chaos-based techniques have been suggested to develop secure image encryption. This study presents a novel image encryption framework based on integrating the chaotic maps and color codes. Three phases are involved in the proposed image encryption technique. Piecewise chaotic linear map (PWLCM) is used in the first phase for permuting the digital image. In the second phase, substitution is done using Hill cipher which is the mixing of color codes with the permuted image. The third phase is implemented by XORing, a sequence generated by the chaotic logistic map (CLM). The proposed approach enhances the diffusion ability of the image encryption making the encrypted images resistant to the statistical differential attacks. The results of several analyses such as information entropy, histogram correlation of adjacent pixels, unified average changing intensity (UACI), number of pixel change rate (NPCR), and peak signal-to-noise ratio (PSNR) guarantee the security and robustness of the proposed algorithm. The measurements show that the proposed algorithm is a noble overall solution for image encryption. Thorough comparison with other image encryption algorithms is also carried out.

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.

The multi-scroll hyper-chaotic coexistence attractors and its application

Applying a chaotic system to digital image communication is an effective way to resist the attack of intelligent system with strong computing power. However, the traditional chaotic systems lack more complex dynamic behavior that is very valuable for a series of applications. Based on Lorenz system, this study proposes a hyper-chaotic system with multi-scroll coexistence attractors by using a piecework function. Through bifurcation diagram and Lyapunov exponents, we analyzed the dynamic behavior of the system, and observed multi-scroll coexistence attractors in the numerical simulation. The results show that compared with the traditional chaotic attractor, multi-scroll coexistence attractor has more complex structure and dynamic behavior. Furthermore, we design a cryptosystem based on this system for the digital image. Scrambling and diffusing images with the sequence of multi-scroll coexistence attractors can destroy the correlation of adjacent pixels and hide the information of all pixels. Theoretical analysis and simulation on key space, histogram, information entropy, key sensitivity and pixel correlation show that the encryption scheme is feasible and secure.

Image encryption scheme with bit-level scrambling and multiplication diffusion

As the most effective method of multimedia security protection, image encryption is widely used in data hiding, security authentication and content protection. However, the security and efficiency are still the key issues of image encryption algorithm. In this paper, a grayscale image encryption scheme based on the architecture of bit-level scrambling and multiplication diffusion is proposed. Firstly, the input image is decomposed into eight bit planes and randomly divided into three parts. Secondly, the scrambling process of each part is respectively realized by using binary tree, flip scrambling and improved circle index scrambling. Finally, the diffusing operation of the scrambled components is executed by improving the GF (257) domain multiplication. The remarkable advantage of the scrambling operation is that it not only effectively permutes the pixels, but also permutes the bits in each pixel, and consequently it sufficiently destroys the correlation of adjacent pixels. And the parallel processing of different scrambling operations will increase the confusion effect and real-time performance. Moreover, the key stream for scrambling and diffusion operations is designed and selected strictly dependent on the plain-image. Therefore, our encryption scheme significantly improves the security by disturbing known-plaintext and chosen-plaintext attacks. Simulation experiments and security analyses further verify that the proposed algorithm is secure and effective to withstand various attacks.

A Novel Image Encryption Algorithm Based on Bernoulli Shift Map

This paper puts forward a chaotic encryption algorithm based on Bernoulli Shift Map. This algorithm adopts dynamic encryption key and uses plaintext image parameters to control generation of chaotic key, and enhance connection between chaotic key and plaintext data; the iterative operation precision of chaotic map during encryption is high, avoiding cycle of chaotic system iteration process. The NPCR and UACI analysis, adjacent pixels correlation analysis and image information entropy analysis on encrypted image show this encryption algorithm has favorable encryption characteristics such as larger space for key, sensitivity to plaintext and random distribution of ciphertext.

Chaotic Deep Network for Mobile D2D Communication

Device-to-Device (D2D) communication has now become one of the most promising technologies in wireless communications of the Internet of Things (IoT). In view of the requirements on data security, response speed, signal decryption quality and storage cost of mobile devices in D2D networks, we propose chaotic deep network (CDN) to achieve secure transmission which is swifter, higher quality and lower cost. The proposed scheme consists of a prepositive nonrepetitive training procedure, a well-designed parallel encryption process, and a set of pretrained chaotic deep neural decryption networks. Benefiting from the utilization of deep learning methods, CDN achieves the swift and accurate decryption at a much lower sampling rate, which brings huge dimension reduction of both measurement matrices and ciphertext signals. Also, chaotic initial values and parameters are applied to matrix generation and network training, leading to great time reduction, storage saving and security improvement. In addition, CDN incorporates the frameworks of semitensor product (STP) and block-based image processing (BIP), which not only breaks through the dimension matching limitation of matrix multiplication by using STP but also maintains the parallelizable block-cipher mode of BIP. Proved by experiments, CDN at the sampling ratio of 25% achieves almost the same or even better peak signal to noise ratio compared to other 8 most frequently used methods at that of 50% for the same test images, and obtains better visual effects. When using a large-sized image of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2^{10}\times 2^{10}$ </tex-math></inline-formula> pixels for the experiments, CDN is dozens and even hundreds of times faster than those methods, while reduces the size of measurement matrix from a 500-kB level to a 3-kB level, and the size of compressed data to be transmitted can be reduced by more than 50% as well. Besides, the total key space is approximately <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{93}$ </tex-math></inline-formula> . The adjacent pixel correlation is less than 0.01.

Three [formula omitted]-secret image sharing schemes based on homogeneous linear recursion

In this paper, three novel secret image sharing schemes based on homogeneous linear recursion are introduced. Simple sharing, various methods for the recovery, small shadow image size and high resolution are some of the merits of our schemes. Moreover, shadow images generated in schemes 2 and 3 are unrevealing and are secured against attacks based on correlation of adjacent pixels, without any need to perform extra computations such as permutation or encryption, which usually were used in the previous schemes.

A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos

Aerial photography involves capturing images from aircraft and other flying objects, including Unmanned Aerial Vehicles (UAV). Aerial images are used in many fields and can contain sensitive information that requires secure processing. We proposed an innovative new cryptosystem for the processing of aerial images utilizing a chaos-based private key block cipher method so that the images are secure even on untrusted cloud servers. The proposed cryptosystem is based on a hybrid technique combining the Mersenne Twister (MT), Deoxyribonucleic Acid (DNA), and Chaotic Dynamical Rossler System (MT-DNA-Chaos) methods. The combination of MT with the four nucleotides and chaos sequencing creates an enhanced level of security for the proposed algorithm. The system is tested at three separate phases. The combined effects of the three levels improve the overall efficiency of the randomness of data. The proposed method is computationally agile, and offered more security than existing cryptosystems. To assess, this new system is examined against different statistical tests such as adjacent pixels correlation analysis, histogram consistency analyses and its variance, visual strength analysis, information randomness and uncertainty analysis, pixel inconsistency analysis, pixels similitude analyses, average difference, and maximum difference. These tests confirmed its validity for real-time communication purposes.

An effective image compression–encryption scheme based on compressive sensing (CS) and game of life (GOL)

At present, information entropies of cipher images gotten by some CS-based image cryptosystems are lower than 7, which make them vulnerable to entropy attack. To cope with this problem, we propose a novel image compression–encryption method based on compressive sensing (CS) and game of life (GOL). Encryption architecture of permutation, compression and diffusion is utilized. Firstly, a plaintext-dependent game-of-life-based scrambling method is presented to shuffle the sparse coefficient matrix of plain image, and the permutation matrix is constructed by rules of GOL, which may effectively reduce the adjacent pixel correlation and enhance the scrambling effect. Secondly, the confused matrix is compressed by CS and diffused using a key matrix to get the cipher image. Additionally, a five-dimensional (5D) memristive hyperchaotic system is used to generate chaotic sequences. They are utilized to construct measurement matrix, to generate initial cell matrix of GOL and to produce key matrix. Information entropy of plain image and external key parameters are combined to compute initial values of the hyperchaotic system. Therefore, our algorithm has high sensitivity to original image and it may resist against known-plaintext attack and chosen-plaintext attack. Experimental results and performance analyses demonstrate that the proposed encryption algorithm is effective to withstand various typical attacks, and it may be applied for image secure communication.

Fast image encryption algorithm with high security level using the Bülban chaotic map

In the last decades, a big number of image encryption schemes have been proposed. Most of these schemes reach a high-security level, however, their slow speeds due to their complex process make them unusable in real-time applications. Motivated by this, we propose a new efficient and high-speed image encryption scheme based on the Bulban chaotic map. Unlike most of the existing schemes, we make a wisely use of this simple chaotic map to generate only a few numbers of random rows and columns. Moreover, to further increase the speed, we raise the processing unit from the pixel level to the row/column level. Security of the new scheme is achieved through a substitution-permutation network, where we apply a circular shift of rows and columns to break the strong correlation of adjacent pixels. Then, we combine the XOR operation with the Modulo function to mask the pixels values and prevent any leak of information. High-security tests and simulation analysis have been carried out to demonstrate that the scheme is extremely secure and highly fast for real-time image processing at 80 fps (frames per second).