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This paper presents a new 4D chaotic system by extending a 3D system to investigate chaotic systems² with hidden attractors further and explore their engineering applications in color image encryption. The system has hyperbolic shape equilibriums and the equilibriums are nonhyperbolic which is interesting and rarely mentioned before. The system has been investigated deeply by phase plot, time series, the largest Lyapunov exponent, bifurcation diagram, Poincaré map and 0–1 test. A coexisting hidden attractor has been found in this new system and the circuit simulation model of the system is built by Power Simulation (PSIM). Circuit simulation results are consistent with results of numerical simulations which verify its dynamic behavior further. Then, by combining the generalized Arnold transform with the new chaotic system, a new color image encryption algorithm has been proposed which has large key space and can encrypt either square images or nonsquare images with different size. Finally, the results of encryption experiment and security analysis prove the effectiveness of the algorithm.

Nowadays, multimedia applications are extensively utilized and communicated over Internet. Due to the use of public networks for communication, the multimedia data are prone to various security attacks. In the past few decades, image watermarking has been extensively utilized to handle this issue. Its main objective is to embed a watermark into a host multimedia data without affecting its presentation. However, the existing methods are not so effective against multiplicative attacks. Therefore, in this paper, a novel quantum-based image watermarking technique is proposed. It initially computes the dual-tree complex wavelet transform coefficients of an input cover image. The watermark image is then scrambled using Arnold transform. Thereafter, in the lower coefficient input the watermark image is embedded using quantum-based singular value decomposition (SVD). Finally, the covered image is obtained by applying the inverse dual-tree complex wavelet transform on the obtained coefficients. Comparative analyses are carried out by considering the proposed and the existing watermarking techniques. It has been found that the proposed technique outperforms existing watermarking techniques in terms of various performance metrics.

Steganography refers to hiding a secret message from various sources, such as images, videos, audio and so on. The advantage of steganography is to avoid data hacking in transmission medium during the transmission of information sources. Video steganography is superior to image steganography since the videos can hide a substantial quantity of secret messages more than the image. Hence, this research introduced the video stereography technique, Arnold Transform with SqueezeNet-based Pelican Whale Optimization Algorithm (AT$+$SqueezeNet_PWOA), for concealing the secret image on the video. To hide the secret image on the video, the proposed method follows three steps: key frame and feature extraction, pixel prediction and embedding. The extraction of the key frame process is carried out by the Structural Similarity Index Measure (SSIM), and then the neighborhood features and convolutional neural network (CNN) features are extracted from the frame to improve the robustness of the embedding process. Moreover, the pixel prediction is completed by the SqueezeNet model, wherein the learning factors are tuned by the PWOA. In addition, the embedding process is completed by applying the Arnold transform on the predicted pixel, and the transformed regions are combined with the secret image using the embedding function. Likewise, the extraction process extracts the secret image from the embedded video by substituting the predicted pixel and Arnold transform on the embedded video. The proposed method is used to hide chunks of secret data in the form of video sequences and it improves the performance. The Arnold transform used in this work provides security by encrypting the data. The use of SqueezeNet makes the proposed model a simple design and this reduces the computational time. Thus, the AT$+$SqeezeNet_PWOA attained better correlation coefficient (CC), peak signal-to-noise ratio (PSNR) and mean square error (MSE) of 0.908, 48.66 and 0.001 dB with the Gaussian noise.

In this paper, we aim to investigate the security of multiple images based on affine hill cipher (AHC), fractional discrete cosine transform (FrDCT) and Arnold transform (AT). Three original $RGB$ images are encoded as a single $RGB$ image by first converting three $RGB$ images into three indexed images by extracting their color maps. These three indexed image are treated as $R$, $G$ and $B$ channel of a single $RGB$ image. Each channel is first encrypted using cryptographic encryption scheme AHC in time domain. The partially encoded image is transformed to frequency domain using FrDCT. In frequency domain, the partially encoded image is scrambled with the help of AT. The proposed scheme assures security in time domain, frequency domain as well as in coordinate domain. The original images can be recovered correctly by using proper arrangements of secret keys. The storage and transmission of the encrypted image is easy due to single encrypted image. The robustness of the proposed approach is proved by conducting computer simulations on standard examples.

In order to deal with the problem of encryption algorithms being overly simplistic, and the relatively low security of color images that creates potential to be attacked in the transmission process, this paper will introduce a new encryption algorithm that is designed to divide color images into R, G and B layers. In the scrambling operation: the first scrambling is aimed to block the clear text image scrambling; The second scrambling is the dynamic Arnold scrambling of the ciphertext after the first scrambling. In the diffusion operation, the scrambled ciphertext image was taken as the input, and the pseudo-random sequence generated by Tent mapping and Sine mapping was embedded. The sequence generated by Logistic mapping was used to select sub-blocks for block diffusion of the image. Tent-Sine mapping was applied to the second diffusion to obtain the final ciphertext image. The algorithm designed in this paper combines image block scrambling and dynamic Arnold scrambling, the scrambling degree of each layer of image pixels would be greatly improved, thus improving the security of color images. In the process of diffusion, chaos sequence is selected for diffusion operation, which increases the difficulty of decoding ciphertext. The simulation results show that the new algorithm has desirable encryption effect, strong key sensitivity and large key space, and complex encryption algorithm can effectively resist attacks, which certainly has value in image information security.

The present paper proposes a discrete cosine transform (DCT) domain watermarking scheme by exploiting nonlinear dynamical saturating detectors in the design of a watermark detection process. A binary copyright character, i.e. watermark to be hidden into an image, is firstly reordered into a binary zig-zag sequence, and then mapped onto the pulse amplitude modulated signal. A certain desynchronization time delay can be deliberately placed into one code of the modulated signal, and is tolerated due to the superior robustness of nonlinear detectors over matched filters. A selected set of DCT coefficients of a host image in a mid frequency range is shuffled by the Arnold transform, which makes it look more like background noise with respect to the watermark signal. Then, the watermark signal is embedded in the set of shuffled DCT coefficients. The copyright character can be extracted by a nonlinear saturating detector without prior knowledge of the original image and watermark, i.e. blind watermark detection. Interestingly, a higher match between the original watermark character and the extracted one can be further achieved by a parallel array of nonlinear detectors via the mechanism of array stochastic resonance. Robustness of the proposed watermarking scheme is shown in the presence of noise, filtering, cropping, and compression.

A fragile watermarking scheme based singular value decomposition (SVD) and Arnold transform is proposed for the integrity authentication of biometric images via computer network. We exploit singular values of singular value decomposition of biometric images to check the integrity of biometric images. In order to make authentication data, the singular values are changed to the binary bits using modular arithmetic. The binary bits of authentication data are embedded into the least significant bit (LSB) of the original biometric image. The pixels to be changed are randomly selected in the original biometric image. The advantages of this scheme are that 1) we can detect any modification of watermarked biometric images, 2) the quality of watermarked biometric images is very high because only a few bits of authentication data are embedded. Experimental results show that the proposed fragile watermarking scheme can be applied to the integrity authentication systems based on biometric image.