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This paper presents an image encryption scheme with data and appearance security, by adopting inter-intra-block scrambling and weighted diffusion. The 2D robust hyper-chaotic map with flexible geometric distribution and rich hyper-chaotic parameter space is employed to generate the key stream for encryption, by considering the characteristics of plaintext. The plain image is first preprocessed by Huffman coding for getting compressed image. Then, the compressed image is divided into four sub-blocks and is further permuted by the designed inter-intra-block scrambling scheme, which can improve the scrambling effect by making the pixel far away from the original adjacent pixels. After that, a weighted diffusion method strongly related to plaintext and key stream is introduced to diffuse the shuffled image to obtain the noise-like cipher image. And in pursuit of higher security, the meaningless noise-like image is embedded into host image to create the visually meaningful cipher image. A series of experiment tests and analyses are carried out to further demonstrate the excellent performances of the encryption scheme. [ABSTRACT FROM AUTHOR]

With the rapid development of multimedia technology and the massive accumulation of user data, a huge amount of data is rapidly generated and shared over the network, while the problems of inappropriate data access and abuse persist. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data in an encrypted domain and accurately extracts the embedded data without affecting the original content. However, the amount of embedded data has been one of the major limitations in the performance and application of RDHEI. Currently, the main approaches to improve the capacity of RDHEI are either to increase the overall capacity or to reduce the length of the auxiliary information. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the overall capacity, we propose a multi-prediction, called MED+GAP predictor, to generate the label map data of non-reference pixels prior to image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels in order to reduce the embedding length of the auxiliary information used for the extraction and recovery. Experiments show that the proposed method with MED+GAP predictor and adaptive Huffman coding improves 0.052 bpp, 0.023 bpp, and 0.047 bpp on average over the other state-of-the-art methods on the BOSSBase, BOWS-2, and UCID datasets, respectively, while maintaining security and reversibility. [ABSTRACT FROM AUTHOR]

Recently, with the rapid development of cloud storage, secure cloud computing and privacy protection have attracted widespread attention. Reversible data hiding in encrypted images (RDHEI) plays an important role in it and has been paid more and more attention. In this paper, an improved RHDEI is proposed. By combining adaptive Arithmetic coding and static Huffman coding, the image bit-plane is effectively compressed and a lot of space is made for data embedding. The security of image and embedded data is guaranteed by XOR-encryption and scrambling encryption. The data extractor can embed and extract data without decrypting the carrier image to protect the privacy of the image owner. Experimental results show that the scheme can achieve an average embedding capacity (EC) of up to 3 bpp while ensuring lossless recovery of carrier images and correct extraction of embedded data. Compared with state-of-the-art RDHEI methods, our scheme achieves higher EC and better security. [ABSTRACT FROM AUTHOR]

In the recent couple of years, due to the accelerated popularity of the internet, various organizations such as government offices, military, private companies, etc. use different transferring methods for exchanging their information. The Internet has various benefits and some demerits, but the primary bad mark is security of information transmission over an unreliable network, and widely uses of images. So, Steganography is the state of the art of implanting a message in the cover objects, that nobody can suspect or identify it. Therefore, in the field of cover steganography, it is very critical to track down a mechanism for concealing data by utilizing different blends of compression strategies. Amplifying the payload limit, and robustness, and working on the visual quality are the vital factors of this research to make a reliable mechanism. Different cover steganography research strategies have been recommended, and each adores its benefits and impediments but there is a need to foster some better cover steganography implements to accomplish dependability between the essential model of cover steganography. To handle these issues, in this paper we proposed a method in view of Huffman code, Least Significant Bits (LSB) based cover steganography utilizing Multi-Level Encryption (MLE) and colorless part (HC-LSBIS-MLE-AC) of the picture. It also used different substitution and flicking concepts, MLE, Magic matrix, and achromatic concepts for proving the proficiency, and significance of the method. The algorithm was also statistically investigated based on some Statistical Assessment Metrics (SAM) such as Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Normalized Cross Correlation (NCC), Structural Similarity Index Metric (SSIM), etc. and different perspectives. The observational outcomes show the likelihood of the proposed algorithm and the capacity to give unwavering quality between security, payload, perception, computation, and temper protection. [ABSTRACT FROM AUTHOR]

Data-hiding technology plays an important role in fields of the image such as copyright identification and annotation. Predicators may be exploited in RDH in the encrypted image (RDHEI); this has become a research interest in recent years because of the development of cloud computing and a need for content owner privacy. The existing algorithms cannot implement large embedding capacity and good reconstructed image quality simultaneously. Consequently, for secure data image transfer, the article suggested the High-Capacity Reversible Data Hiding in Encrypted Images (RDH-EI) approach. The original image was pre-processed by the content owner to free up hiding space in the RRBE scheme, following which the image will be encrypted and transferred to the data hider. Asymmetric encryption is considered to be more secure than symmetric encryption as it uses two keys for the process. Initially, to offer authenticity and integrity, Elliptic Curve Cryptography (ECC) is proposed to encrypt, decrypt, and authenticate the cipher image. This requires much shorter key lengths and was highly efficient in the decryption process. Further, the encrypted images are directed to the data hiding process. A considerable amount of data is employed to embed in the image encryption domain to ensure that the embedded data can be extracted error-free. Subsequently, to have high embedding capacity, the research proposed Multi-MSB (Most Significant Bit) data embedding scheme in which secret bits can be directly extracted from the encrypted domain from the pixels without any error. In addition, to retain image quality by employing both reference and context pixels, a near-lossless solution based on the Huffman Coding technique is proposed. With the use of decryption and a data concealing key, the receiver can restore the original image and extract hidden data afterwards. The keys are made in such a way that the decryption key cannot be easily deduced from the public encryption key. The experiment was carried out in MATLAB software using a built-in function. The findings reveal that the suggested method outperforms conventional RDH strategies in terms of PSNR and embedding with 3.6 bpp respectively. In addition, the algorithm can resist steganalysis attacks, and demonstrated the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

We propose a method of secure and reversible data hiding in encrypted images which ensures lossless recovery of image contents and data with very high embedding capacity. The proposed reversible data hiding method in encrypted images makes use of median edge detector predictor and Huffman coding for reducing the size of axillary information. The proposed method utilizes the spatial correlation of the image for reserving room for data embedding before encryption. Hiding capacity of each 2 × 2 block in the image is calculated based on the prediction error using the median edge detector. The hiding capacities of adjacent four blocks are labeled using Huffman coding, which reduces the size of the auxiliary information hidden along with secret data embedded in the encrypted image. Proposed method does data hiding without changing the characteristics of encrypted image for ensuring security and recovers data and image contents completely. The experimental results show that the proposed method hides higher payload with an average value of 3.34 bpp which is 25 percentage more than the state of the art methods. [ABSTRACT FROM AUTHOR]

As an interesting technique that allows data extraction and image recovery without any loss, reversible data hiding in encrypted images is an area of great concern in the field of information security. In this paper, a new reversible data hiding method with high embedding capacity is proposed based on hybrid prediction and Huffman coding. The combination of two embedding mechanisms is innovatively designed to improve the embedding capacity according to different parts of the original image, i.e., the most significant bit-plane and the remaining seven bit-planes. In the first part of this method, the prediction value of each pixel is obtained by calculating the average value of its two neighboring pixels, and all of the most significant bits can be vacated to accommodate additional data. In the second part, the prediction value of each pixel is calculated using the median edge detector predictor, on which the tag map is built. Then, Huffman coding is used to compress the tag map so that a large amount of vacant space is obtained. Finally, the secret data can be embedded into the vacated space by directly using bit substitution. Compared with some recently reported methods, experimental results and analysis have demonstrated that an original image with high visual symmetry/quality can be recovered. Also, larger embedding capacity can be achieved, such as 3.3894 bpp and 3.2824 bpp, for BOSSBase and BOWS2 databases, respectively. [ABSTRACT FROM AUTHOR]

Steganography is the practice of hiding data, such as images, videos, or text, within a cover image without it being detectable by the human eye. Several factors, such as the capacity, security, and robustness of the technique, are essential when transferring information using this method. In this study, we propose a new approach to image steganography that improves the Least Significant Bit (LSB) technique by utilizing images of 24 bits in each pixel. Improving the capacity and security of LSB-based steganography requires a combination of techniques, such as indirect embedding, embedding in multiple channels, and applying cryptographic and compression techniques. This approach conducts by encrypting each compressed secret message bit with the most significant bit of the red channel and then saving the output bit (hidden bit) in the least significant bit of the (green/blue) channel according to the row value (odd/ even). To further security, the suggested approach uses multi-level encryption; employs RSA to encrypt the secret message before applying the Huffman compression and encrypting the hidden bit by (XOR/XNOR) in the embedding method based on the row value of the pixel. Meanwhile, it is planned to use the Huffman coding technique to shorten the length of the encrypted message that will be inserted in the cover image. For the color photos in this work, the standard images were acquired from a standard dataset (USC-SIPI). The suggested approach performs better when measured in terms of mean square error (MSE), peak signalto- noise ratio (PSNR), and comparison to findings from related prior efforts. [ABSTRACT FROM AUTHOR]

As the rapid development of third-party storage and homomorphic encryption have profoundly stimulated the desire for secure communication, reversible data hiding in encrypted images has received widespread attention, since it allows lossless data conveying and perfect image recovery. In order to obtain secure reversible data hiding with high embedding capacity, a novel block embedding method is proposed, based on an adaptive recognition strategy for combined blocks in the binary image, with which the adjacent identical blocks can be integrated into a combination to reserve more spare bits for data accommodation. Furthermore, a fully reversible data hiding method for grayscale images in the encryption domain is designed. The secret data is hidden into lower bit-planes of the image while the original bits of those embedded lower pixels are recorded into the vacated space of higher bit-planes. The original image can be reconstructed flawlessly as well as the secret data being extracted without errors. To reinforce security, the original image and the secret data are encrypted and scrambled based on sequences generated with the high-dimension chaotic system. Due to its high sensitivity of initial values, the performance such as security and robustness is guaranteed. By comparing the PSNR value of the marked decrypted image and evaluating the quality of the extracted secret image, experimental results demonstrate that the proposed method can obtain higher embedding capacity, achieving 0.2700–0.3924 bpp increment over the state-of-the-art methods, and recover the marked decrypted image with high visual symmetry/quality, and efficiently resist against potential attacks, such as the histogram analysis, differential, brute-force, JPEG attacks, and so on. [ABSTRACT FROM AUTHOR]

This paper proposes a novel image compression‐encryption scheme based on compressive sensing and bit‐level XOR. In the proposed scheme, the encrypted sequences are generated from a 4‐D hyper‐chaotic Lorenz system and a Logistic system. First, an original image is sampled by a secure block parallel compressive sensing (PCS) scheme. In the PCS phase, a key‐controlled discrete cosine transform sparse basis matrix and a key‐controlled complex Hadamard measurement matrix are employed. Next, the real part and imaginary part of the resulting complex‐valued data are quantized and transformed into bit streams, respectively. After that, the two generated bit streams are combined into one bit stream. Then, the resulting bit stream is further encrypted by a bit‐level XOR operation, where the encrypted key is generated from a chaotic system. The experiment results show the effectiveness and reliability of the proposed joint compression‐encryption scheme. The proposed scheme can not only enhance the security of the compressed image but also improve the reconstructed quality of the compressed image. [ABSTRACT FROM AUTHOR]

To achieve privacy protection and effective management in cloud computing, and solve the problem of existing reversible data hiding in encrypted image (RDH-EI) algorithms being unable to resist existing various attacks, an RDH-EI algorithm based on key-controlled balanced Huffman coding (KBHC) is proposed. The novelty lies in KBHC and variable-length bit scrambling. KBHC possesses non-preset, balanced, and key-controlled characteristics, providing the proposed algorithm with high capacity and enhanced security. The non-preset allows coding tables to be adaptively generated based on prediction error maps, resulting in shorter encoded streams for higher embedding capacity. The balanced characteristic is achieved by adjusting the subtrees, so that the balance rate in the encoded stream is 0.014, and can also reach 0.065 for particularly smooth images, achieving uniform distribution of the encoded stream, thereby improving the ability to resist statistical analysis attacks. The random key controls the leaf nodes scrambling in the Huffman tree, which realizes the variability of the encoded stream and avoids the potential security risks caused by timestamp reconstruction, laying the foundation to achieve differential attack security. Variable-length bit scrambling determines the pseudo-random extension length and scrambling sequence by both the encryption key and coding table information, effectively resists brute force attacks and ensures up to 100 % difference rate between scrambling sequences generated in each run. Experimental results demonstrate that compared to several RDH-EI methods, the proposed algorithm achieves higher embedding capacity and security under acceptable complexity. The average embedding rate of three databases reaches 3.897 bpp, and the proposed algorithm effectively resists statistical analysis attacks, COA, KPA, and differential attack. [ABSTRACT FROM AUTHOR]

The Asymmetric Numeral System (ANS) is a new entropy compression method that the industry has highly valued in recent years. ANS is valued by the industry precisely because it captures the benefits of both Huffman Coding and Arithmetic Coding. Surprisingly, compared with Huffman and Arithmetic coding, systematic descriptions of ANS are relatively rare. In 2017, JPEG proposed a new image compression standard—JPEG XL, which uses ANS as its entropy compression method. This fact implies that the ANS technique is mature and will play a kernel role in compressing digital images. However, because the realization of ANS involves combination optimization and the process is not unique, only a few members in the compression academia community and the domestic industry have noticed the progress of this powerful entropy compression approach. Therefore, we think a thorough overview of ANS is beneficial, and this idea brings our contributions to the first part of this work. In addition to providing compact representations, ANS has the following prominent feature: just like its Arithmetic Coding counterpart, ANS has Chaos characteristics. The chaotic behavior of ANS is reflected in two aspects. The first one is that the corresponding compressed output will change a lot if there is a tiny change in the original input; moreover, the reverse is also applied. The second is that ANS compressing an image will produce two intertwined outcomes: a positive integer (aka. state) and a bitstream segment. Correct ANS decompression is possible only when both can be precisely obtained. Combining these two characteristics helps process digital images, e.g., art collection images and medical images, to achieve compression and encryption simultaneously. In the second part of this work, we explore the characteristics of ANS in depth and develop its applications specific to joint compression and encryption of digital images. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted images (RDHEI) is a technology that embeds data directly in the encrypted images without decryption or knowledge of the content of the images. However, it is difficult to vacate room from the encrypted image. This problem limits the embedding capacity of the existing RDHEI methods. In this paper, we propose a new RDHEI method designed to supply large embedding capacity without pre-processing of the original images. Using a block-level encryption scheme, the proposed method partially retains the spatial correlation in the high bit-planes of the encrypted image, while the content of the image is held securely. The data hider can compress the high bit-planes of the encrypted image to vacate high-capacity room using Huffman compression coding. In addition, image recovery and data extraction are separable and error-free at the receiver side. The receiver can retrieve the lossless original image without the embedded data using only an encryption key or by extracting the secret data directly from the encrypted image without decryption using only the data-hiding key. The experimental results and comparison proved that the proposed method performs better than previous methods in terms of embedding capacity and visual quality. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted domain (RDH-ED) is widely used for ensuring the security of content, protecting privacy, and facilitating the management of digital media stored in the cloud. However, research on the application of RDH-ED technology in 3D mesh model carriers is still in its infancy. This paper proposes a reversible data hiding scheme based on Ring Co-XOR encryption (RCXOR) to address the challenges with the existing RDH-ED algorithms for 3D mesh models. Specifically, the proposed scheme eliminates the need to transmit auxiliary information to a third party and increases the embedding capacity. First, the original 3D mesh model is divided into m non-overlapping rings, where different rings do not share vertices. Next, m sets of random bitstreams are generated based on the encryption key. Within each ring, the vertices are encrypted using bitwise XOR with the same random bitstream. This preserves redundancy between adjacent vertices within the same ring in the encrypted data. Finally, a multi-MSB prediction method based on the ring vertex is proposed using the RCXOR encryption technique. To this end, the ring center vertex (RCV) serves as the reference vertex for predicting the multi-MSB of the ring edge vertex (REV), creating space for data hiding. The Canonical Huffman Coding method is used to compress the label and obtain the optimal embedding capacity for data hiding. The experimental results demonstrate that the proposed algorithm surpasses the current vacating room after encryption (VRAE)-based methods in terms of embedding ability, achieving an average embedding rate of 25.63 bits per voxel (bpv) on the dataset, compared to 6 bpv for the state-of-the-art approach. • We proposed a new ring Co-XOR encryption (RCXOR) method for 3D mesh model. • We propose a multi-MSB prediction method based on the ring center vertex to achieve high-capacity reversible data hiding. • We have demonstrated the security of the proposed RCXOR encryption through experiments and mathematics. • The proposed algorithm achieves a higher embedding rate compared to state-of-the-art algorithms based on the VRAE framework. [ABSTRACT FROM AUTHOR]

The popularity of cloud computing has impelled more users to upload personal data into the cloud server. The need for secure transmission and privacy protection has become a new challenge and has attracted considerable attention. In this paper, we propose a high-capacity reversible data hiding scheme in encrypted images (RDHEI) that compresses prediction errors in usable blocks of block-based encrypted images. On the content owner side, the original image is divided into 2 × 2 sized blocks, and each block is encrypted by block-based modulation. On the data hider side, an efficient block-based predictor is utilized to generate prediction errors. The Huffman coding technique is introduced to compress prediction errors in the usable blocks to embed abundant additional data. On the receiver side, the additional data can be totally extracted with a data hiding key and the original image can be losslessly recovered with an image encryption key. Experimental results demonstrate that the embedding rate of our proposed scheme is significantly improved compared to those of state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

The recent advancements in the internet technology have created the urgency in developing critical data security framework around the globe. One of the most shared multimedia objects is the image which is safeguarded through a task called image encryption. An integrated approach to image encryption is the need of the hour which can combine algorithm and communication model. In this context, this work presents the first- of- its- kind approach addressing Elliptic Curve Cryptography (ECC) to encrypt and decrypt the images to enhance their security during transmission via Single Carrier Frequency Division Multiple Access (SC-FDMA) communication systems. The uniqueness of this work is to combine the encryption scheme and subsequent wireless transmission. Modified Huffman coding has been employed to achieve compression. The viability of the proposed approach was tested and the performance metrics namely Entropy, PSNR, Histogram, correlation coefficient, differential attack, NIST test, and occulation attack analyses were evaluated. The simulation results prove the efficiency of the proposed integrated encryption – compression – communication schema. [ABSTRACT FROM AUTHOR]

In this research, a joint image compression and encryption scheme is presented which works for different image dimensions 256X256, 512X512 and 1024X1024 and different image sizes. The proposed scheme is efficient as compression and encryption is done simultaneously which makes computations faster and secure at the same time. The compression scheme deployed is like JPEG compression but uses column-wise scanning and optimization instead of zigzag scanning. In entropy phase coding, Huffman coding of JPEG compression is replaced with Arithmetic coding. Image encrypted using XOR encryption is unbreakable, as used earlier in one-time pad. Compressed data is XORed with randomly generated number. The proposed scheme is implemented for grayscale images using MATLAB software version 2016a. The experimental results showed that the scheme provides good compression ratio, secures against attacks and takes less computation time. This can be further extended for RGB images of different dimension 256X256, 512X512 and 1024X1024 and different image sizes. [ABSTRACT FROM AUTHOR]

• A retrieval scheme based on the Huffman code of encrypted JPEG images. • The scheme ensures the encrypted image is confidentiality, integrity and JPEG-format compatibility. • After QT conversion, the retrieval is feasible for encrypted images of varying QFs. • Through sharing the secret key, the dilemma of effective retrieval and feature leakage is solved. This paper proposes a retrieval scheme for encrypted JPEG images, based on Huffman code in the JPEG bitstream. Three parties are involved: content owner, cloud server, and authorized user. First, the content owner produces encrypted images by jointly using a stream cipher, permutation cipher, then uploads them to a cloud server. Especially, the conversion between encrypted quantization tables is still valid. With the same secret key, the authorized user submits the encrypted query image to the server. Second, the server extracts Huffman-code histogram from the encrypted image as a feature. Although the Huffman-code histogram is changed during encryption, encrypted images with similar content to the query image are returned to the user after feature comparison. Finally, through decryption and hash verification, the user can obtain authenticated plaintext images. Experimental results show that the proposed scheme ensures confidentiality, integrity and format compatibility, while image retrieval of different quality factors is still effective. [ABSTRACT FROM AUTHOR]

This paper proposes a novel reversible data hiding (RDH) algorithm with differential compression (DC) in encrypted image, which has high embedding capacity. The key contributions are two sides. (1) An efficient block-based encryption scheme is developed for encrypting image. It can transfer spatial correlation between neighboring pixels of plaintext image into encrypted image. (2) The DC scheme is proposed to conduct compression of encrypted image. It can efficiently compress encrypted image by exploiting pixel correlation and vacate a large room for data embedding. Many experiments are conducted to evaluate the performance of our RDH algorithm. Comparisons illustrate that our RDH algorithm outperforms some state-of-the-art algorithms in embedding capacity and computational time. [ABSTRACT FROM AUTHOR]

This paper proposes a joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform. A new five-dimensional hyperchaotic system based on the Rabinovich system is presented. By means of the proposed hyperchaotic system, a new pseudorandom key stream generator is constructed. The algorithm adopts diffusion and confusion structure to perform encryption, which is based on the key stream generator and the proposed hyperchaotic system. The key sequence used for image encryption is relation to plain text. By means of the second generation curvelet transform, run-length coding, and Huffman coding, the image data are compressed. The joint operation of compression and encryption in a single process is performed. The security test results indicate the proposed methods have high security and good compression effect. [ABSTRACT FROM AUTHOR]

In this paper we investigate information-theoretic image coding techniques that assign longer codes to improbable, imprecise and non-distinct intensities in the image. The variable length coding techniques when applied to cropped facial images of subjects with different facial expressions, highlight the set of low probability intensities that characterize the facial expression such as the creases in the forehead, the widening of the eyes and the opening and closing of the mouth. A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effective platform for future emotion categorization experiments. [ABSTRACT FROM AUTHOR]

Since different regions of an image have different importance, therefore only the important information of the image regions, which the users are really interested in, needs to be encrypted and protected emphatically in some special multimedia applications. However, the regions of interest (ROI) are always some irregular parts, such as the face and the eyes. Assuming the bulk data in transmission without being damaged, we propose a chaotic image encryption algorithm for ROI. ROI with irregular shapes are chosen and detected arbitrarily. Then the chaos-based image encryption algorithm with scrambling, S-box and diffusion parts is used to encrypt the ROI. Further, the whole image is compressed with Huffman coding. At last, a message authentication code (MAC) of the compressed image is generated based on chaotic maps. The simulation results show that the encryption algorithm has a good security level and can resist various attacks. Moreover, the compression method improves the storage and transmission efficiency to some extent, and the MAC ensures the integrity of the transmission data. [ABSTRACT FROM AUTHOR]

To achieve a high embedding capacity (EC) without any distortion in the directly decrypted result, a reversible data hiding in encrypted images (RDH-EI) scheme based on full bit-plane compression (FBPC) is proposed. FBPC is designed to vacate as much room as possible before image encryption. To enrich the adjacent redundancy within the most significant bit (MSB) planes, we use flip prediction on the first MSB and then replace the other MSB planes with the XOR result between that plane and its higher level one successively. Hilbert curve scanning is introduced to reduce the dimensionality of the planes to obtain eight highly redundant bit sequences. Huffman coding is then utilizing to compress the bit sequences. After FBPC, a compressed image is obtained. Stream cipher with self-feedback is adapted to encrypt the image. Additional data could be embedded into the reserved space of the encrypted domain. Compared with existing RDH-EI algorithms, the proposed scheme could have a higher EC with no distortion in the directly decrypted image due to the high compression performance of FBPC. Experimental results on the BOWS-2 and BOSSbass datasets demonstrate that the average EC can reach 3.56 and 3.71 bits per pixel, respectively. [ABSTRACT FROM AUTHOR]

We propose an optical security method for object authentication using photon-counting encryption implemented with phase encoded QR codes. By combining the full phase double-random-phase encryption with photon-counting imaging method and applying an iterative Huffman coding technique, we are able to encrypt and compress an image containing primary information about the object. This data can then be stored inside of an optically phase encoded QR code for robust read out, decryption, and authentication. The optically encoded QR code is verified by examining the speckle signature of the optical masks using statistical analysis. Optical experimental results are presented to demonstrate the performance of the system. In addition, experiments with a commercial Smartphone to read the optically encoded QR code are presented. To the best of our knowledge, this is the first report on integrating photon-counting security with optically phase encoded QR codes. [ABSTRACT FROM PUBLISHER]

Reversible data hiding in encrypted images (RDHEI) is a technology which embeds secret data into encrypted images in a reversible way. In this paper, we proposed a novel high-capacity RDHEI method which is based on the compression of prediction errors. Before image encryption, an adaptive linear regression predictor is trained from the original image. Then, the predictor is used to obtain the prediction errors of the pixels in the original image, and the prediction errors are compressed by Huffman coding. The compressed prediction errors are used to vacate additional room with no loss. After image encryption, the vacated room is reserved for data embedding. The receiver can extract the secret data and recover the image with no errors. Compared with existing approaches, the proposed method efficiently improves the embedding capacity. [ABSTRACT FROM AUTHOR]

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new reversible data hiding method in encrypted images. Due to spatial correlation, there is a large probability that the adjacent pixels of the image have small differences, which is especially obvious on the high four most significant bits (high nibbles) of the pixels. If the high nibble of each pixel is regarded as a 4-bit value, the differences between the high nibbles of the adjacent pixels are mostly concentrated in a small range. Based on this fact, Huffman coding was used to encode all the differences between the high nibbles of the adjacent pixels in order to compress the four most significant bit (MSB) planes efficiently and create a large-capacity room. After creating room, a stream cipher is used to encrypt the image, and the room is reserved in the encrypted image for data hiding without losing information. The experimental results showed that the proposed method can achieve a larger embedding rate and better visual quality of the marked decrypted image than other related methods. [ABSTRACT FROM AUTHOR]