A color image encryption algorithm based on an improved Hénon map

A color image encryption and decryption scheme based on extended DNA coding and fractional-order 5D hyper-chaotic system

Images are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color image sector fast encryption algorithm based on one-dimensional composite sinusoidal chaotic mapping. The main purpose of this algorithm is to improve the encryption and decryption speed of color images and improve the efficiency of image encryption in the big data era. First, four basic chaos maps are combined in pairs and added with sine operations. Six one-dimensional composite sinusoidal chaos maps (CSCM) were obtained. Secondly, select the two best chaotic mappings LCS and SCS. The randomness of these two chaotic mappings was verified through Lyapunov index and NIST SP 800-22 randomness tests. Thirdly, the encryption process is carried out according to the shape of a traditional Chinese fan, and the diffusion and scrambling of each pixel of the image are performed in parallel. This greatly improves encryption speed. When diffusing, changing the value of one pixel can affect the values of multiple subsequent pixels. When scrambling, each pixel changes position with the three pixels before it according to the chaotic sequence. Finally, through many experiments, it is proved that the image encryption algorithm not only greatly improves the encryption and decryption speed, but also improves various indexes. The key space reached 2192, the average information entropy was 7.9994, the average NPCR was 99.6172, and the average UACI was 33.4646. The algorithm can also resist some common attacks and accidents, such as exhaustion attack, differential attack, noise attack, information loss and so on.

A novel devaney chaotic map with uniform trajectory for color image encryption

A color image encryption algorithm by combining the reality-preserving fractional DCT (RPFrDCT) with chaotic mapping in HSI space is presented, in which the generating sequence (GS) is introduced and produced by 2D chaotic mapping to ensure the uniqueness of the transform matrix and enlarge the cipher key space of the encryption system. In addition, the color image is converted from standard RGB space into HSI space and the nonlinearity of the spatial transform makes the proposed encryption algorithm more secure than linear ones. Three components, namely H, S and I, are encrypted by the RPFrDCT with fractional orders and GS as cipher keys. Three-dimensional (3D) scrambling is adopted to further enhance the security of the encryption algorithm. The nonlinearity of the spatial transform from RGB to HSI, the real-valued output and the high cipher key-sensitivity guarantee the security and the feasibility of the proposed encryption algorithm. Experimental results demonstrate that the proposed encryption algorithm is sensitive to cipher keys and, to some extent, robust to noise and occlusion attacks.

A novel color image encryption algorithm based on a cross 2D hyperchaotic map is proposed in this paper. The cross 2D hyperchaotic map is constructed using one nonlinear function and two chaotic maps with a cross structure. Chaotic behaviors are illustrated using bifurcation diagrams, Lyapunov exponent spectra, phase portraits, etc. In the color image encryption algorithm, the keys are generated using hash function SHA-512 and the information of the plain color image. First, the color plain image is converted to a combined bit-level matrix and permuted by the chaos-based row and column combined cycle shift scrambling method. Then, the scrambled integer matrix is diffused according to the selecting sequence which depends on the chaotic sequence. Last, decompose the diffusion matrix to get the encrypted color image. Simulation experiments and security evaluations show that the algorithm can encrypt the color image effectively and has good security to resist various kinds of attacks.

With the development of the Internet, the amount of information carried in images is gradually increasing, and image encryption algorithms for data transmission have been developed. The conventional composite chaotic sequence encryption algorithm has the problem of too long convergence speed when applied to images, which can lead to the risk of information leakage in the image. To address this issue, this study first applies chaotic attractors to improve composite chaotic sequences and enhance the search domain of their Leia Index. At the same time, the Arnold transform technology is introduced into the expert monitoring system, and the two systems are fused to generate a fusion algorithm for color image encryption. Finally, the study conducts experiments on the Differ dataset to verify the effectiveness and superiority of the fusion algorithm, and compares it with three algorithms such as artificial fish schools. The image encryption times of the four algorithms are 6 s, 16 s, 29 s, and 33 s respectively, indicating that the fusion algorithm has the highest encryption speed. When facing exhaustive attacks, the image information damage degrees of the four algorithms are 0.014, 0.051, 0.172, and 0.184, respectively. The experimental results show that the proposed algorithm can effectively resist differential attacks and exhaustive attacks, and is suitable for encrypting color images.

Image encryption based on 3D Cubic-Sine Logistic Coupled Map and Improved Chirikov Map

Color image encryption has enticed a lot of attention in recent years. Many authors proposed a chaotic system-based encryption algorithms for that purpose. However, due to the shortcomings of the low dimensional chaotic systems, similar rule structure for RGB channels, and the small keyspace, many of those were cryptanalyzed by chosen-plaintext or other well-known attacks. A Security vulnerability exists because of the same method being applied over the RGB channels. This paper aims to introduce a new three-channel three rules (3C3R) image encryption algorithm along with two novel mathematical models for DNA rule generator and bit inversion. A different rule structure was applied in the different RGB-channels. In the R-channel, a novel Block-based Bit Inversion (BBI) is introduced, in the G-channel Von-Neumann (VN) and Rotated Von-Neumann (RVN)- based 2D-cellular structure is applied. In the B-channel, a novel bidirectional State Machine-based DNA rule generator (SM-DNA) is introduced. Simulations and results show that the proposed 3C3R encryption algorithm is robust against all well-known attacks particularly for the known-plaintext attacks, statistical attacks, brute-force attacks, differential attacks, and occlusion attacks, etc. Also, unlike earlier encryption algorithms, the 3C3R has no security vulnerability.

Image encryption based on chaotic maps is an important method for ensuring the secure communication of digital multimedia on the Internet. To improve the encryption performance and security of image encryption systems, a new image encryption algorithm is proposed that employs a compound chaotic map and random cyclic shift. First, a new hybrid chaotic system is designed by coupling logistic, ICMIC, Tent, and Chebyshev (HLITC) maps. Comparison tests with previous chaotic maps in terms of chaotic trajectory, Lyapunov exponent, and approximate entropy illustrate that the new hybrid chaotic map has better chaotic performance. Then, the proposed HLITC chaotic system and spiral transformation are used to develop a new chaotic image encryption scheme using the double permutation strategy. The new HLITC chaotic system is used to generate key sequences used in the image scrambling and diffusion stages. The spiral transformation controlled by the chaotic sequence is used to scramble the pixels of the plaintext image, while the XOR operation based on a chaotic map is used for pixel diffusion. Extensive experiments on statistical analysis, key sensitivity, and key space analysis were conducted. Experimental results show that the proposed encryption scheme has good robustness against brute-force attacks, statistical attacks, and differential attacks and is more effective than many existing chaotic image encryption algorithms.

Security of image data is essential during communication from various security attacks. This paper proposed a new technique for RGB color image encryption and decryption by the combination of shuffling and masking. The chaotic Baker map is used for first layer of image encryption by randomizing the pixels of each components of color image such as red, green and blue and then applying the diffusion process i.e. fractional dual random phase masks (FDRPM) technique which is applied on each component to increase the security level of given method. The order of Discrete Fractional Fourier Transform (DFRFT) act as a key for the process which provides extra degree of security to the proposed system. Matlab simulations are performed to check the security robustness of proposed scheme. Performance of proposed scheme is verified by noise analysis such as mean square error (MSE) and various differential analysis such as Unified Average Change Intensity (UACI) and Number of Pixels Change Rate (NPCR). Results of various analysis shows that the novel proposed encryption technique shows high efficiency and security for color images.

In this paper, a cellular neural network (CNN) chaotic system is constructed and the multiple stability of the system and its rich chaotic properties are confirmed by studying the effect of parameters on the system, coexisting attractors, and offset boosting behavior. As linear feedback shift registers (LFSR) can be applied to cryptography, this paper applies LFSR to generate encrypted key matrices to enhance the randomness of encryption algorithms. Based on CNN and LFSR, a new color image encryption algorithm is designed by combining DNA coding and bit-plane decomposition with high bit-plane Zigzag dislocation changes. Experimental results and security tests show that the algorithm is highly secure and resistant to a variety of common attacks, such as differential attacks, cropping attacks, and noise attacks.

Multi-wing chaotic systems are highly valued for their complexity and pseudo-randomness, making them promising in applications like secure communication and image encryption. However, existing chaotic systems face limitations in attractor diversity and system dimensions, which restrict their effectiveness in complex encryption applications. In this paper, we construct a four-dimensional multi-wing chaotic system based on the Sprott-A chaotic system by introducing linear feedback control and additional state variables. Furthermore, by incorporating piecewise linear functions and new state variables, a five-dimensional multi-wing chaotic system with the characteristic of odd and even numbers of hidden attractors are developed. Odd multi-wing attractors have centrally symmetric complex trajectories, while even multi-wing attractors possess axisymmetric trajectories through the introduction of offset terms. This system overcomes the limitations of existing chaotic systems and significantly improves complexity, controllability, and pseudo-randomness, making it more suitable for encryption applications. Based on this system, we design a new color image encryption algorithm that uses chaotic sequences for pixel permutation and diffusion operations. The security analysis indicates that the algorithm offers a large key space, high sensitivity to initial conditions, and strong resistance to various attacks, providing a novel solution for complex encryption applications.

Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them. In the paper, a novel color image encryption algorithm is introduced. The 24 bit planes of components R, G, and B of the color plain image are obtained and recombined into 4 compound bit planes, and this can make the three components affect each other. A four-dimensional (4D) memristive hyperchaotic system generates the pseudorandom key streams and its initial values come from the SHA 256 hash value of the color plain image. The compound bit planes and key streams are confused according to the principles of genetic recombination, then confusion and diffusion as a union are applied to the bit planes, and the color cipher image is obtained. Experimental results and security analyses demonstrate that the proposed algorithm is secure and effective so that it may be adopted for secure communication.

To enhance image privacy protection and reduce storage space, this paper proposes an image compression and encryption algorithm that combines compressed sensing, Hachimoji DNA coding, and a 7D hyperchaotic system. The algorithm processes the high-frequency and low-frequency parts after the wavelet transform separately. Sparse high-frequency information is compressed by low-compression measurement. The low-frequency part uses block-compressed sensing, and only a small amount of data is needed to reconstruct a high-quality image. In addition, the measurement matrix is constructed by chaotic sequence, which reduces the demand for memory and transmission bandwidth. To protect compressed data, this paper also presents an image encryption algorithm based on Hachimoji DNA dynamic coding and Joseph dynamic traversal. The algorithm first uses Joseph traversal to disturb the bit position of each pixel dynamically and then implements Hachimoji DNA dynamic coding. At the same time, a new Joseph bidirectional dynamic scrambling-diffusion algorithm is proposed, which gives the encrypted image a uniform grayscale histogram, high information entropy, and sensitivity to resist various attacks effectively.

Color image encryption and authentication algorithm integrating computational ghost imaging with quaternion multi-parameter discrete fractional angular transform