Encrypted Pixels Research Articles

Improved vigenere using affine functions surrounded by two genetic crossovers for image encryption

This paper presents an improved method for encrypting color images, surpassing the effectiveness of genetic crossover and substitution operations. The technique incorporates dynamic random functions to enhance the integrity of the resulting vector, increasing temporal complexity to thwart potential attacks. The improvement involves integrating genetic crossover and utilizing two extensive pseudorandom replacement tables derived from established chaotic maps in cryptography. Following the controlled vectorization of the original image, our approach initiates with a first genetic crossover inspired by deoxyribonucleic acid (DNA) behavior at the pixel level. This genetic crossover is succeeded by a confusion-diffusion lap, reinforcing the connection between encrypted pixels and their neighboring counterparts. The confusion-diffusion process employs dynamic pseudorandom affine functions at the pixel level. Then a second genetic crossover operator is applied. Simulations conducted on a diverse set of images with varying sizes and formats showcase the robustness of our method against statistical, brute-force, and differential attacks.

Enhanced Vigenere and affine ciphers surrounded by dual genetic crossover mechanisms for encrypting color images

This paper introduces an enhanced technique for encrypting color images, surpassing the effectiveness of genetic crossover and substitution methods. The approach integrates dynamic random functions to bolster the integrity of the resulting vector, elevating temporal complexity to deter potential attacks. The enhancement entails amalgamating genetic crossover using two extensive pseudorandom replacement tables derived from established chaotic maps in cryptography. Following the controlled vectorization of the original image, our method commences with an initial genetic crossover inspired by DNA behavior at the pixel level. This process is followed by a confusion-diffusion lap, strengthening the relationship between encrypted pixels and their neighboring counterparts. The confusion-diffusion mechanism employs dynamic pseudorandom affine functions at the pixel level. Subsequently, a second genetic crossover operator is applied. Simulations conducted on various images with varying sizes and formats demonstrate the resilience of our approach against statistical and differential attacks.

An efficient Intra-Inter pixel encryption scheme to secure healthcare images for an IoT environment

Digital images are being frequently used for diagnosis in clinics today. Diagnostic images with identifying patient data are stored and transmitted across open networks. Security measures are therefore becoming more and more crucial to safeguard the confidentiality of sensitive patient data. In medical imaging, adjacent pixels show a strong degree of connection. This paper presents an efficient intra-inter bit-level pixel operation-based image encryption method that eliminates pixel correlation and provides strong security. In this method, after gathering medical image data from IoT sensors, the intra bit-level pixel permutation and diffusion operations are executed separately and in parallel in each of the bit planes, and the inter bit-level pixel permutation and diffusion operations are then performed in the concatenated bit-planes. The bit-level operation not only permutes but also diffuses the pixels at the same time. As a result, the security of the algorithm is increased by executing several pixel permutations and diffusions. In addition to this, the approach is effective due to the parallel execution of bit-plane permutation and diffusion. The simulation results and the security analysis indicate the superior performance of the proposed algorithm.

An Ensemble Learning Approach for Reversible Data Hiding in Encrypted Images with Fibonacci Transform

Reversible data hiding (RDH) is an active area of research in the field of information security. In RDH, a secret can be embedded inside a cover medium. Unlike other data-hiding schemes, RDH becomes important in applications that demand recovery of the cover without any deformation, along with recovery of the hidden secret. In this paper, a new RDH scheme is proposed for performing reversible data hiding in encrypted images using a Fibonacci transform with an ensemble learning method. In the proposed scheme, the data hider encrypts the original image and performs further data hiding. During data hiding, the encrypted image is partitioned into non-overlapping blocks, with each block considered one-by-one. The selected block undergoes a series of Fibonacci transforms during data hiding. The number of Fibonacci transforms required on a selected block is determined by the integer value that the data hider wants to embed. On the receiver side, message extraction and image restoration are performed with the help of the ensemble learning method. The receiver will try to perform all possible Fibonacci transforms and decrypt the blocks. The recovered block is identified with the help of trained machine-learning models. The novelty of the scheme lies in (1) retaining the encrypted pixel intensities unaltered while hiding the data. Almost every RDH scheme described in the literature alters the encrypted pixel intensities to embed the data, which represents a security concern for the encryption algorithm; (2) Introducing an efficient means of recovery through an ensemble model framework. The majority of votes from the different trained models guarantee the correct recovery of the cover image. The proposed scheme enables reduction in the bit error rate during message extraction and contributes to ensuring the suitability of the scheme in areas such as medical image transmission and cloud computing. The results obtained from experiments undertaken show that the proposed RDH scheme was able to attain an improved payload capacity of 0.0625 bits per pixel, outperforming many related RDH schemes with complete reversibility.

A MapReduce Based Approach for Secure Batch Satellite Image Encryption

The overarching goal of this research was to examine the state of satellite imagery security in relation to its deteriorating form due to rising demand. The most common approaches to safeguarding satellite images during transmission across transmission networks, which are not protected by standard encryption, are the focus of this investigation. Since satellite imagery can be encrypted both in transit and while stored on a computer’s hard drive, we put the suggested Image Encryption System to the test by applying it to a collection of satellite photos. Concurrently encrypting data and running MapReduce jobs is key to the study methodology employed. This will be carried out in the Hadoop ecosystem, where an innovative method of analysing random numbers for use in Image encryption will be put to the test. The encryption was processed using MapReduce in the Hadoop ecosystem. Images were saved as BMP files with added security metadata. The evaluation of experiments was based on four (4) indicators. It was found that the processing time for batch encryption calculations grew in proportion to the amount of computations. All cluster, map, and reduction processes were put to the test using encrypted images, exposing load balancing difficulties and inefficiencies. Histogram analysis, the basis of an image encryption technique, provides evidence that the encrypted pixel values are consistent. Therefore, compared to other methods, such as a histogram or information entropy, this one is superior. Because of how it was crafted, it can withstand even the most sophisticated attacks without being compromised.

High-capacity reversible data hiding in encrypted images based on pixel-value-ordering and histogram shifting

New security threats are generated with the coming of information industrial 5.0 represented by artificial intelligence and Industrial Internet of Things (IIoT). One of the most significant concerns in IIoT is information security which refers to the protection of the privacy of image owner. To this end, a new reversible data hiding in encrypted image (RDHEI) method with high capacity for IIoT security is proposed in this paper. On image owner side, image contents are protected by a block level image encryption method while the correlations of adjacent pixels inside the same block are not damaged. On receiver side, to realize reversibility, all encrypted pixel blocks are classified into overflow blocks and non-overflow blocks and only non-overflow blocks are used to carry additional data. Then, some secret data, which is used to manage encrypted images, is embedded into the largest and smallest pixels in non-overflow blocks by utilizing pixel-value-ordering and histogram shifting techniques. On the receiver side, original image and secret data can be recovered perfectly. Moreover, according the availability of decryption key and data hiding key, image recovery and data extraction are separably executed. Experimental results demonstrate that significant improvement in embedding capacity is achieved without destroying reversibility. In this way, the proposed method outperforms several state-of-the-art methods and it is quite suitable for IIoT.

New Chaotic System: M-Map and Its Application in Chaos-Based Cryptography

One of the applications of dynamical systems with chaotic behavior is data encryption. Chaos-based cryptography uses chaotic dynamical systems as the basis for creating algorithms. The present article discusses a new dynamical system called M-map with its analysis: fixed points, bifurcation diagram, Lyapunov exponent, and invariant density. The obtained bifurcation diagram and the plot of the Lyapunov exponent (with a minimum value of ln2 and a maximum value of ln4) suggest that the so-called robust chaos characterizes this map. Moreover, the obtained results are compared with other dynamical systems used in cryptography. Additionally, the article proposes a new image encryption algorithm. It uses, among others, cyclically shifted S-box or saving encrypted pixels on the first or last free space in the cipher-image. The conducted analysis shows that the cipher-images are characterized by an entropy value close to 8, a correlation of adjacent pixels value close to 0, or values of Number of Pixel of Change Rate (NPCR) and Unified Average Changing Intensity (UACI) measures close to 100% and 33%, respectively.

CFB-Then-ECB Mode-Based Image Encryption for an Efficient Correction of Noisy Encrypted Images

During the last few decades, the transmission of images over secure networks has exponentially grown. Data security in certain applications such as secure storage, authentication or privacy protection on cloud platforms, require specific strategies for multimedia. Cryptography can be used for this purpose. Indeed, using a secret key, it is possible to make data unreadable in order to secure it. Although encryption approaches are effective to make the original data unreadable, they are also very sensitive to noise. Because of the introduction of noise into an encrypted image during its transmission or storage, the original data cannot be recovered. In this article, we first describe a new encryption mode called CFB-then-ECB and based on a combination of the CFB mode and the ECB mode for AES encryption. Using this new encryption mode, if one encrypted pixel block is noised, this will result in two incorrectly reconstructed pixel blocks during the decryption (the current and the following pixel blocks). This noise spreading is then exploited in a new proposed approach of noisy encrypted image correction. It contains two main steps involving a classifier to discriminate clear and encrypted pixel blocks. After a direct decryption of a noisy encrypted image, the first step is to identify and localize the pixel blocks that are probably incorrectly decrypted. The second step of our proposed approach is to analyze and correct these pixel blocks. Experimental results show that the proposed method can be used to blindly correct noisy encrypted images, while preserving the image structure without increasing the original data size with additional information.

Research on intelligent recognition and encryption algorithm of network big data image

In view of the identification and encryption of massive network information in the era of big data, this paper proposes to use intelligent image recognition technology to analyze the required information, then classify it according to the big data clustering method, and use pseudo pixel encryption algorithm for multiple encryption. The simulation results show that the algorithm has high recognition rate, good encryption effect, strong anti-interference ability and good ability to protect network image information.

Quantum image encryption algorithm based on generalized Arnold transform and Logistic map

In the era of big data, image security and real-time processing become more and more important and increasingly difficult to satisfy. To improve the security and processing efficiency of image encryption algorithm, an enhanced quantum scheme is proposed for generalized novel enhanced quantum image representation. The proposed quantum encryption scheme mainly consists of two-stage operation in order, i.e., twice scrambling based generalized Arnold transform and pixel encryption based on the quantum key image (which are generated and prepared based on Logistic map). In the first stage, generalized Arnold transform are employed to simultaneously disturb the coordinate information and pixel gray value of quantum plain image. Following that, the scrambled image is further encrypted into a quantum cipher image based on quantum key image, which is divided into three sub-processes in detail, i.e., CNOT operations, bit-plane scrambling and controlled perfect shuffle permutations are executed orderly. The quantum image decryption process can be easily implemented in a reverse way. The complete quantum circuit implementation for above two stages operation is constructed and analyzed in terms of quantum cost and time complexity. Compared to classical image processing algorithm, the investigated quantum encryption algorithm demonstrates an exponential speedup with computational cost of $${\rm O}\left( n \right)$$ for a $$2^{n} \times 2^{n}$$ quantum grayscale or color images. The proposed scheme is simulated and verified on a classical computer with MATLAB environments, i.e., not in a real quantum version that not considers the effects of quantum noise. Experimental results and numerical analysis indicate that the presented quantum algorithm has good visual effects and high security.

A Novel Secure Occupancy Monitoring Scheme Based on Multi-Chaos Mapping

Smart building control, managing queues for instant points of service, security systems, and customer support can benefit from the number of occupants information known as occupancy. Due to interrupted real-time continuous monitoring capabilities of state-of-the-art cameras, a vision-based system can be easily deployed for occupancy monitoring. However, processing of images or videos over insecure channels can raise several privacy concerns due to constant recording of an image or video footage. In this context, occupancy monitoring along with privacy protection is a challenging task. This paper presents a novel chaos-based lightweight privacy preserved occupancy monitoring scheme. Persons’ movements were detected using a Gaussian mixture model and Kalman filtering. A specific region of interest, i.e., persons’ faces and bodies, was encrypted using multi-chaos mapping. For pixel encryption, Intertwining and Chebyshev maps were employed in confusion and diffusion processes, respectively. The number of people was counted and the occupancy information was sent to the ThingSpeak cloud platform. The proposed chaos-based lightweight occupancy monitoring system is tested against numerous security metrics such as correlation, entropy, Number of Pixel Changing Rate (NPCR), Normalized Cross Correlation (NCC), Structural Content (SC), Mean Absolute Error (MAE), Mean Square Error (MSE), Peak to Signal Noise Ratio (PSNR), and Time Complexity (TC). All security metrics confirm the strength of the proposed scheme.

A separable reversible data hiding scheme in encrypted image for two cloud servers

This paper presents a separable reversible data hiding in encrypted image (SRDH-EI) based on code division multiplexing (CDM). In this, the owner encrypts the cover image first, and then uploads the preprocessed image to two cloud servers. In the servers, two encrypted pixels, on the same place of uploaded images, form an embedded vector. Finally the secret bits, which are encoded to CDM spreading sequences, are embedded into the vector. At the receiver side, there are three cases: 1) if they only have the data hiding key, the secret bits can be extracted; 2) if they only have the encryption key, the original image can be recovered; 3) if they have the two keys, both of them can be obtained. Compared with the classic dual-images RDH method, the proposed method protects the content security of the outsourced cloud image and has a better performance on visual quality and embedding capacity.

A Fast Chaotic Image Encryption Scheme With Simultaneous Permutation-Diffusion Operation

In this paper, a secure and fast chaotic image encryption scheme with simultaneous permutation-diffusion operation is proposed. We combine permutation and diffusion processes into a whole, namely, simultaneous permutation and diffusion operation (SPDO). This can solve the problem of traditional encryption scheme in which the permutation and diffusion are two independent processes, that leads attackers to crack the two processes separately. In SPDO, the initial value of the current Sine-Sine chaotic map is related to the secret keys and the previous encrypted pixels’ values. In this case, the proposed scheme can generate dynamic key streams and indexes that are related to plaintext, which improves the sensitivity to plaintext for the encryption scheme. In addition, the pixel values are processed by row and column (row-level and column-level) during the encryption procedure. Thus, the proposed scheme presents lower time complexity and faster running speed compared with bit-level or pixel-level image encryption schemes, which makes the proposed scheme be conducive to the batch transmission and real-time transmission of digital images. The simulation results and security analysis show that our scheme can resist common attacks, such as statistical attack, differential attack, chosen plaintext attack and other comprehensive attacks.

Algorithm of ensuring confidential data security of the cloud medical information system

The objectives of the study are to develop and assess the effectiveness of the structure of a cloud platform for storing, processing and organizing medical data, determining a method of protection, in particular, ensuring confidentiality when transferring and storing examination results. The proposed method for protecting a medical information system involves the use of an original DICOM file and subsequently a converted PNG image, which is subjected to a pixel encryption algorithm. An algorithm based on chaos theory is used to encrypt the image. The capabilities of chaos systems can significantly increase productivity. Hierarchical division of data streams into levels and standardization of data transmission protocols, as well as their storage formats, allow to form a universal, flexible and reliable medical information system. The proposed architecture has the ability to integrate into existing medical systems. In the course of the work, it was found that the considered protection method is an effective way to ensure the confidentiality of medical system data.

A novel color image encryption algorithm based on substitution box and hyper-chaotic system with fractal keys

In this paper, a novel color image encryption scheme based on fractals, substitution box and hyper chaotic dynamic is proposed. In the first step, fractal images are generated by Julia fractal set as keys. Then, the substitution box is constructed by Hilbert fractal, and the original image pixels are replaced with the values of the S-box. In the next step, using the Logistic map, the location of the pixels is scrambled to reduce their correlation. In the following, Chen hyper-chaotic system is used to change the pixels values of fractal images as well as index production to select fractal images. Finally, each pixel of three original image layers with the corresponding pixels in the three selected fractal images and the previous encrypted pixel value are encrypted with XOR operation. Both experimental results and security analyses indicated that the proposed method yields high encryption effect, larger secure key space and is high sensitive to the secret key and the plain image. In addition, the algorithm could resist against diverse typical attacks.

Secret Image Sharing using 2-Pixel Visual Cryptography Encryption

Visual Cryptography Scheme (Vcs) Is A Procedure For Encrypting Visual Data Such As Hand-Written Text, Image, Digital Text, Captured Image Etc. In This Scheme, The Shares Are Generated By Scrambling The Pixels Of The Original Image. Further, These Shares Are Sent To Receiver For Decryption At The Receiver End. In this paper, we have proposed an automated tool that takes the binary image as an input, and generates initial shares with one pixel encryption algorithm. Further, these initial shares are encrypted using 2-pixel encryption algorithm. The encrypted shares are then sent to the receiver for decryption to obtain the initial shares. The receiver then stacks the shares to get the original image. The proposed work which is presented in the methodology is the extension of VCS algorithm.

An Improved Reversible Data Hiding in Encrypted Images Using Parametric Binary Tree Labeling

This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image but not in small image blocks to reserve room for hiding data. Then the original image is encrypted with an encryption key and the parametric binary tree is used to label encrypted pixels into two different categories. Finally, one of the two categories of encrypted pixels can embed secret information by bit replacement. According to the experimental results, compared with several state-of-the-art methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.

Flexible Lossy Compression for Selective Encrypted Image With Image Inpainting

In this paper, a novel lossy compression scheme for encrypted image based on image inpainting is proposed. In order to maintain confidentiality, the content owner encrypts the original image through a modulo-256 addition encryption and block permutation to mask image content. Then, the third party, such as a cloud server, can compress the selective encrypted image before transmitting to the receiver. During compression, encrypted blocks are categorized into four sets corresponding to different complexity degrees in plaintext domain without the loss of security. By allocating various bit rates to the encrypted blocks from different sets, flexible compression can be achieved with difference quantization. After parsing and decoding the compressed bit stream, the receiver first recovers partial encrypted pixels and then decrypts them. The other missing pixels are further recovered with the assistance of image inpainting based on a total variation model, and the final reconstructed image can be produced. Experimental results demonstrate that the proposed scheme achieves better rate-distortion performance than some of the state-of-the-art schemes.

Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction

In this paper, we propose a separable reversible data hiding method in encrypted image (RDHEI) based on two-dimensional permutation and exploiting modification direction (EMD). The content owner uses two-dimensional permutation to encrypt original image through encryption key, which provides confidentiality for the original image. Then the data hider divides the encrypted image into a series of non-overlapping blocks and constructs histogram of adjacent encrypted pixel errors. Secret bits are embedded into a series of peak points of the histogram through EMD. Direct decryption, data extraction and image recovery can be performed separately by the receiver according to the availability of encryption key and data-hiding key. Different from some state-of-the-art RDHEI methods, visual quality of the directly decrypted image can be further improved by the receiver holding the encryption key. Experimental results demonstrate that the proposed method outperforms some state-of-the-art methods in embedding capacity and visual quality.

Reversible Data Hiding Scheme in Homomorphic Encrypted Image Based on EC-EG

To combine homomorphic public key encryption with reversible data hiding, a reversible data hiding scheme in homomorphic encrypted image based on EC-EG is proposed. Firstly, the cover image is segmented. The square grid pixel group randomly selected by the image owner has one reference pixel and eight target pixels. The n least significant bits (LSBs) of the reference pixel and all bits of target pixel are self-embedded into other parts of the image by a method of predictive error expansion (PEE). To avoid overflowing when embedding data, the n LSBs of the reference pixel are reset to zero before encryption. Then, the pixel values of the image are encrypted after being encoded onto the points of the elliptic curve. The encrypted reference pixel replaces the encrypted target pixels surrounding it, thereby constructing the mirroring central ciphertext (MCC). In a set of MCC, the data hider embeds the encrypted additional data into the n LSBs of the target pixels by homomorphic addition in ciphertexts, while the reference pixel remains unchanged. The receiver can directly extract additional data by homomorphic subtraction in ciphertexts between the target pixels and the corresponding reference pixel; extract the additional data by subtraction in plaintexts with the directly decrypted image; and restore the cover image without loss. The experimental results show that the proposed scheme has higher security than the similar algorithms, and the average embedding rate of the scheme is 0.25 bpp under the premise of ensuring the quality of the directly decrypted image.