An improved visually meaningful encrypted image scheme

Hiding information in an image in a way that does not affect the original cover image pixels or cause a permanent distortion after extracting that information is known as reversible data hiding technology. Many reversible data hiding schemes have been proposed and successfully applied in medical and military applications. Such schemes are developed to ensure digital images' authenticity and integrity without any distortion on the original images. They guarantee that any attempt to change the watermarked image will be detected by the image owner. In this paper, a novel algorithm is proposed to reversibly hide data into encrypted grayscale medical images in a separable manner. The proposed algorithm hides two watermarks in a given encrypted image. The first watermark is embedded by replacing selected encrypted image pixels based on data hiding key, and the second watermark is embedded in the watermarked encrypted image using the histogram shifting reversible data hiding method. The experimental results demonstrate that the proposed algorithm has high embedding capacity, high visual image quality, and high entropy.

At present, with the rapid development of science and technology and the rapid development of computer related technology, with the development of this series of technologies, multimedia communication has rapidly become the means of communication and communication. Digital image technology, a very important form of information representation in multimedia communication, has now become a mainstream way. The technology provides more convenience for people's lives, but also has many problems, such as security, transmission and storage. For example, some images will involve personal privacy, business secrets, and even government secrets. In addition, the rapid transmission of information in limited bandwidth is also very important. Especially in the presence of cloud storage, it can not only store large amounts of information, such as files, videos and images, but also provide a large enough online space to store shared data. In this case, the real-time and security requirements of information transmission are higher and stricter. It is of great theoretical and practical significance to compress the image and reduce the bandwidth and ensure the security of image encryption. Image encryption is also called digital image encryption. Image compression is mainly based on the use of different technologies to change the pixel value and location of the image to protect the image. Image compression mainly compresses the image by removing redundant or unrelated information. In this paper, the concept of the variational self encoder is introduced firstly, and then the image compression and encryption based on the variational self coder generation model are studied and summarized briefly.

This paper proposes a scheme of separable reversible information hiding (RIH) for encrypted images (EIs) in which hidden information can be extracted from an EI carrying information without image decryption. The proposed scheme firstly encrypts an image and simultaneously prepares room for RIH by two permutation ways. Information are, then, hidden into the EI by a RIH technique, and the EI carrying information is sent to a receiver. According to keys which the receiver has, he/she is allowed to take seven different actions, whereas the conventional scheme offers only three. This feature of the proposed scheme extends applicable scenarios. Moreover, the proposed scheme always recover the original image, whereas the conventional scheme sometimes fails to do.

A novel compact image encryption system is proposed based on Arnold transformation (AT). In general, AT is a pixel-scramble tool in image encryption, but its security is not high enough as an independent cryptosystem because of its periodicity. Hence, extra diffusion operations are needed to diffuse the pixel values to acquire the higher security. Here an encryption algorithm is proposed by AT. Firstly, the corresponding coordinates of each pixel in original image are calculated by AT. Secondly, the pixel values of the two corresponding coordinates are disturbed by another AT. These two processes can diffuse the pixel values of the original image. At last, the diffused image is pixel scrambled by AT with different parameters. This is the confusion process. In proposed scheme, the diffusing and confusing operations are both realized by AT. At the same time, the image is encrypted as a pixel distribution instead of a data stream. The key space, key sensitivity, the correlation, the cost time and the security of proposed cryptosystem are analyzed and the results confirm that the proposed image encryption algorithm demonstrates extraordinary performance.

Chaotic image encryption based on circular substitution box and key stream buffer

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

In this paper we propose a hybrid representation of environment models by a point representation augmented to geometric representation of surface polygons reconstructed from multiple reference images, through which a real time walkthrough of a complex environment can be achieved. By the method, we start from classification of pixels of the source images into two categories, corresponding respectively to the planar and non-planar surfaces in 3D space. For the pixels corresponding to the planar surfaces, the plane coefficients are reconstructed and all their appearances in the reference images are merged to form uniformly sampled texture images by a comparison of sampling rate and resampling. For the pixels corresponding to the non-planar surfaces, a point representation is applied and the redundant pixels are removed again through sampling rate comparison. The remained pixels are organized by OBB-tree according to their space coordinates. At the same time, the holes that are unable to be captured by all the reference images are pre-filled in the preprocessing phase so that the probability of hole appearance in walkthrough is greatly reduced. Under this hybrid representation, texture mapping and point warping are employed to render the novel views, to take full advantages of the acceleration utility of graphics hardware.

Many researchers have used the properties of the popular Elliptic Curve Cryptography(ECC) to devise a stronger and faster image encryption algorithm to assure the secrecy of images during online transmission. In this paper, a robust Elliptic curve based image encryption and authentication model for both grayscale and color images has been proposed. The model uses the secure Elliptic Curve Diffie-Hellman(ECDH) key exchange to compute a shared session key along with the improved ElGamal encoding scheme. 3D and 4D Arnold Cat maps are used to effectively scramble and transform the values of plain image pixels. A well-structured digital signature is used to verify the authenticity of the encrypted image prior to decryption. The model produces good-quality cipher images with an average entropy of 7.9993 for grayscale and 7.99925 for the individual components of color images. The model has high average NPCR of 99.6%, average UACI of 33.3% and low correlation for both grayscale and color images. The model has low computational costs with minimized point multiplication operations. The proposed model is robust with high resilience against statistical, differential, chosen-plaintext(CPA), known-plaintext(KPA) and occlusion attacks.

In this paper we analyzed methods of investigating structure features in solid-state materials and developed a new algorithm for determining the surface structural complexity of these materials based on the two-dimensional detrended fluctuation analysis and the scale-space analysis. It is proposed to evaluate the surface structural complexity by calculating tangent of the angle of the fluctuation – spatial scale function and number of breakpoints on the fluctuation – spatial scale function. The developed algorithm was tested on the surface image of the Si layer implanted by Ag<sup>+<?sup> ions, subjected to the pulsed laser annealing. We found that investigated surface belongs to the type of surfaces with a high structural complexity. It was also shown that the scaling index – smoothing coefficient (scale) dependence can be used to study the dynamics of changes in the correlation properties of the surface. Knowledge about surface structural complexity of solid-state materials can be used to determine the material functional purpose in different fields of science.

The formation of Au nanostructures (NSs) under 8 keV Ne+ ion treatment of Au thin film is investigated to explore the involved mechanism using experimental and theoretical approaches. This study is based on atomic force microscopy, Rutherford backscattering spectrometry, and contact angle measurements. The results are discussed in the light of the thermal spike model and tridyn simulation. It is observed in the simulations that Ne ion treatment results in ejection of atoms from the surface due to elastic collision induced transfer of energy and increase in lattice temperature due to the formation of thermal spikes. The effect of ion dose on the surface morphology is also explored using a two-dimensional detrended fluctuation analysis (DFA).The DFA gives information about the fractal dimension (Df) and Hurst exponent (H) of the surface. The fractal dimension (Df) shows that irregularity of a surface is significantly influenced by ion treatment. The contact angle of the water droplet with the surface is discussed with the interface width and fractal dimension. The competition among nuclear sputtering, de-wetting, and diffusion processes results in the formation of NSs. It also demonstrates that the experimental findings are in good agreement with the theoretical results.

Image encryption (IE) is a very useful and popular technology to protect the privacy of users. Most algorithms usually encrypt the original image into an image similar to texture or noise, but texture and noise are an obvious visual indication that the image has been encrypted, which is more likely to cause the attacks of enemy. To overcome this shortcoming, many image encryption systems, which convert the original image into a carrier image with visual significance have been proposed. However, the generated cryptographic image still has texture features. In line with the idea of improving the visual quality of the final password images, we proposed a meaningful image hiding algorithm based on prediction error and discrete wavelet transform. Lots of experimental results and safety analysis show that the proposed algorithm can achieve high visual quality and ensure the security at the same time.

Registration of multi-modal remote sensing images is an essential and challenging task in different remote sensing applications such as image fusion and multi-temporal change detection. Mutual Information (MI) has shown to be successful similarity measure for multi-modal image registration applications, however it has some drawbacks. 1. MI surface is highly non-convex with many local maxima. 2. Spatial information is completely lost in the calculation of the joint intensity probability distribution. In this paper, we present an improved MI similarity measure based on a new concept in integrating other image features as well as spatial information in the estimation of the joint intensity histogram which is used as an estimate of the joint probability distribution. The proposed method is based on the idea that each pixel in the reference image is assigned a weight, then each bin in the joint histogram is calculated as the summations of the weights of the pixels corresponding to that bin. The weight given to each pixel in the reference image is an exponential function of the corresponding pixel values in a distance image and a normalized gradient image such that higher weights are given to points close to one or more selected key points as well as points with high normalized gradient values. The proposed method is in essence a kind of calculating similarity measure using irregular sampling where sampling frequency is higher in areas close to key-points or areas with higher gradients. We have compared the proposed method with the conventional MI and Normalized MI methods for registration of pairs of multi-temporal multi-modal remote sensing images. We observed that the proposed method produces considerably better registration function containing fewer erroneous maxima and leading to higher success rate.

This study introduces a cutting-edge image encryption algorithm aimed at elevating security standards. The Pan-Tompkins Algorithm (PTA) for key generation is proposed for the first time in this study. Additionally, employing steganography through the Least Significant Bit (LSB) method for embedding keys within the encrypted image enhances secure key distribution, thereby fortifying the encryption process. On the other hand, the integration of advanced algorithms, such as Zigzag scanning, the Affine Image Encryption Algorithm (AA), and the Vigenere Image Encryption Algorithm (VA), constitutes the fundamental innovation of the proposed image encryption algorithm. The proposed algorithm is named PanAAVA:Affine Algorithm and Vigenere Algorithm Encryption with PTA-Based Key Generation. The PanAAVA algorithm ensures unparalleled security by encrypting the positions and values of pixels using AA and VA. Notably, using PTA for key generation marks a distinctive and new key generation method feature of the algorithm. To assess the effectiveness of the PanAAVA, a comprehensive comparative analysis is conducted against well-established encryption methodologies, including Lena, Baboon, Airplane, and Pepper.The PanAAVA demonstrates exceptional proficiency in histogram analysis. The PanAAVA demonstrates a Unified Average Changing Intensity (UACI) of 33.4044%. Additionally, the Number of Pixels Change Rate (NPCR) is measured at 99.7442%, showcasing the algorithm’s effectiveness in inducing significant pixel changes. The proposed algorithm’s Mean Square Error (MSE) is calculated at 3.20679E5%. The proposed algorithm’s Peak Signal to Noise Ratio (PSNR) is recorded at 9.512475. The Key Space Size of the proposed algorithm is measured at 2209. Regarding correlation analysis, the PanAAVA achieves a high correlation score of 7.9996. The proposed algorithm successfully passes the National Institute of Standards and Technology (NIST) analysis, demonstrating a remarkably strong correlation close to 0 and a Structural Similarity Index Measure (SSIM) of 0.9977. Furthermore, regarding quantum communication, the proposed algorithm maintains stable key rates of 47.5 ± 0.8 kHz during the day and 50.9 ± 0.7 kHz at night. Additionally, PanAAVA achieves low Quantum Bit Error Rate (QBER) values of 4.77 ± 0.02, ensuring reliable and secure communication. The PanAAVA also demonstrates robust asymmetries at 49.81 ± 0.02 and 50.14 ± 0.03 for a crystal length of 20 mm. highlighting PanAAVA’s adaptability and effectiveness in different scenarios. PanAAVA outperforms other encryption algorithms concerning performance measurements and comparisons. In conclusion, the PanAAVA emerges as a beacon of superior security capabilities and innovation in image encryption, showcasing the potential to redefine standards in the field.

Image encryption converts a meaningful image into some random arrangement of pixel intensities. That means, the intelligible property of an image is destroyed. Taking into consideration excessively large time and space complexity required by the image encryption algorithm using multiple chaotic systems, this paper proposes an image encryption method in which employs three chaotic sequence to achieve fairly high level of encryption. Novelty of the proposed approach lies in the designed algorithm to achieve both permutation and substitution processes of image encryption. In the end, a comparison in the coefficient correlation values is drawn to evaluate the performance of the proposed algorithm with respect to many lately proposed image encryption schemes.

In order to improve the security of reversible data hiding algorithm in encrypted images, Liu designed an image multi-permutation encryption algorithm. By combining bit-plane permutation with pixel-block permutation, the embedding capacity of the algorithm is improved, and the ability of the encryption algorithm to resist existing Ciphertext-Only and Known-Plaintext attack is effectively improved. To analyze the security performance of the encryption algorithm, a Known-plaintext attack method based on the Root Mean Square(RMS) of image block is proposed in this paper. Firstly, the permutation order of bit plane is estimated by using the invariant distribution ratio of 0 and 1 before and after image encryption, the original pixel values is restored. Then, according to the characteristics that the pixel values of the image remain unchanged during block permutation and intra-block pixel permutation, the image block RMS feature is defined to search and estimate the block permutation sequence. Image block RMS equivalence class is defined by the image block RMS value, the ratio of the maximum number of elements in the equivalence class to the total number of pixels is p, which determines the difficulty of known plaintext attack. For the common image test set, 96% of the images have a p-value of less than 0.1, and only 4% of the images have a p-value greater than 0.1. Experimental results show that, When p 0.1, the attacker can crack more than 80% of the image content by two pairs of plaintext and ciphertext.