A separable reversible data hiding scheme for encrypted JPEG bitstreams

With the extensive use of cloud services in different applications, it's a problem for the cloud service provider to manage or process the privacy data that are encrypted by the content owner. Therefore, signal processing technology in the encrypted domain has attracted the attention of researchers. In this paper, we propose a new reversible data hiding method for encrypted images based on two-phase histogram shifting. In the proposed method, the original image is encrypted by using special image division and additive homomorphic encryption. After image encryption, the encrypted image can partially maintain spatial correlation for data embedding while the content security of the encrypted image is ensured. Due to the spatial correlation, the data hider can generate two difference histograms from the encrypted image, which provide high embedding capacity. A two-phase histogram shift scheme is used to embed the secret data into the two difference histograms. At the receiver side, the secret data can be extracted from the encrypted image or the decrypted image, and the image can be recovered to its original version without any error. The experimental results demonstrated that the proposed method can efficiently improve the capacity of data embedding and outperform other related methods, while the visual quality of the marked image can be maintained.

Reversible data hiding over encrypted images (RDH-EI) technology is a viable solution for privacy-preserving cloud storage, as it enables the reversible embedding of additional data into images while maintaining image confidentiality. Since the data hiders, e.g., cloud servers, are willing to embed as much data as possible for storage, management, or other processing purposes, a large embedding capacity is desirable in an RDH-EI scheme. In this article, we introduce a novel bi-directional block encoding (BDBE) method, which, for the first time, encodes the distances of values in a binary sequence from both ends. This approach allows for encoding images with smaller sizes compared to traditional and state-of-the-art encoding methods. Leveraging the BDBE technique, we propose a high-capacity RDH-EI scheme. In this scheme, the content owner initially predicts the image pixels and then employs BDBE to encode the prediction errors, creating space for data embedding. The resulting encoded data are subsequently encrypted using a secure stream cipher, such as the Advanced Encryption Standard, before being transmitted to a data hider. The data hider can embed confidential information within the encrypted image for the purposes of storage, management, or other processing. Upon receiving the data, an authorized receiver can accurately recover the original image and the embedded data without any loss. Experimental results demonstrate that our RDH-EI scheme achieves a significantly larger embedding capacity compared to several state-of-the-art schemes.

Binary coding methods have been widely used for phase unwrapping. However, traditional temporal binary coding methods require a sequence of binary patterns to encode the fringe order information. This paper presents a spatial binary coding (SBC) method that encodes the fringe order into only one binary pattern. Each stripe of the sinusoidal phase-shifting patterns is corresponding to an N-bit codeword of the binary pattern. A robust stripe-wise decoding scheme is also developed to extract the N-bit codeword, then fringe order can be determined, and stripe-wise phase unwrapping can be performed. Experiment results confirm that the SBC method can correctly recover the absolute phase of measured objects with only one additional binary pattern.

Hiding data or information by embedding in a redundant medium like text, audio or video is called as steganography. In ancient time, different techniques such invisible ink, wax tablets, Morse code, etc. were used to send secret information from one place to another. Now in the epoch of digitalization, even the medium for steganography has evolved from paper, wood, etc. to multimedia. Video Steganography is a secure method to embed information in the video frame, but the main drawback of this system is that storing a significant amount of data introduces distortion in the pixels of the frame gets altered which increases the suspicion about the secret data present in it. Traditional techniques used Advance Encryption Standard to encrypt and Least Significant Bit to embed information in the image by modifying the least significant bit of the pixel. However, this introduces distortion in the image which can be recognised by the intruder. Least Significant Bit is not preferred if a substantial quantity of data is to be embedded. In the proposed system, the data is encrypted using Advance Encryption Standard and divided using arithmetic division method. In this approach, the data will be stored in the form of divisor, quotient & remainder. The location key is also distributed, encrypted and stored in different frames. Along with this pixel, pattern matching is also used to avoid distortion of the video frame. This system will be difficult to crack since the location key is divided as well as encrypted and stored in different video frames along with this the secret message is stored in the form of a quotient, a divisor and a remainder. Even if the system is attacked the chance of the intruder to predict the pattern will be difficult as the secret data is embedded with dual protection.

Binary coding methods have been widely used for three-dimensional (3D) shape measurement. However, traditional binary coding methods always require a sequence of binary patterns to encode the fringe order. This paper presents a spatial-temporal binary coding (STBC) method for 3D shape measurement with three binary patterns, including a spatial pattern and two temporal patterns. Specifically, the spatial pattern is used to encode a 4-bit spatial code, and the temporal patterns are used to encode the 2-bit temporal code. By combining the spatial code and the temporal code, 6-bit code words can be obtained that distinguish 26=64 fringe periods of sinusoidal phase-shifting patterns. A robust dual-region labeling decoding scheme is also developed to extract the 6-bit code word for fringe order determination, and then absolute-phase unwrapping can be carried out. Experiments have been conducted, and their results confirm that the STBC method can reliably reconstruct the 3D shapes of measured objects with only three binary patterns.

Reversible data hiding in encrypted images (RDHEI) has been introduced for preserving image privacy and data embedding. RDHEI usually involves three parties, namely, the image provider, data hider, and receiver. On the security with key setting, there are three categories: share independent secret keys (SIK), shared one key (SOK), and share no secret keys (SNK). In SIK, the image provider and data hider must respectively and independently share secret keys with the receiver, whereas in SNK, no secret key is shared. However, the literature works proposed SNK-type schemes by using homomorphic encryption (with exorbitant computation cost). In this paper, we address the SOK setting, where only the image provider shares a secret key with the receiver, and the data hider can embed a secret message without any knowledge of this key. To realize our SOK scheme in a simple manner, we propose a new technique by using multi-secret sharing as the underlying encryption, which indeed induces a blow-up issue of the key size. For preserving the efficiency of the key size, we apply a compression by using lightweight cryptographic algorithms. Then, we demonstrate our SOK scheme based on the proposed techniques, and show effectiveness, efficiency, and security by experiments and analysis.

Existing model-preserving steganography techniques are based on embedding data by modifying least significant bits of a cover image. To keep invariant component of pixel intact only, Least Significant Bit Replacement (LSBR) function is used to modify non-invariant component of the pixel. LSBR is found to be weak against visual or statistical attacks and provide limited steganographic capacity. Least significant Bit Matching (LSBM) embedding provides better security in comparison LSBR but it is not suitable for most of the model-preserving steganographic techniques. This paper explores the possibility of securely embedding data in least two significant bits of the cover image. It is shown that the embedding in least two significant bits violates the assumption of the structural steganalysis tools and techniques available to detect presence of a message in a stego image. Therefore, structural and non-structural detectors fail to detect presence of data in a stego image. The proposed embedding functions result in improved security and steganographic capacity in comparison to LSBM.

With the rapid development of the Internet, preserving the security of confidential data has become a challenging issue. An effective method to this end is to apply steganography techniques. In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. The proposed edge detection scheme partitions the given image, namely cover image, into blocks. Next, it identifies the edge blocks based on the variance of their corner pixels. Embedding the confidential data in sharp edges causes less distortion in comparison to the smooth areas. To diminish the imposed distortion by data embedding in edge blocks, we employ LSB and MPC algorithms. In the proposed scheme, the blocks are split into some groups firstly. Next, a full tree is constructed per group using the LSBs of its pixels. This tree is converted into another full tree in some rounds. The resultant tree is used to modify the considered LSBs. After the accomplishment of the data embedding process, the final image, which is called stego image, is derived. According to the experimental results, the proposed algorithm improves PSNR with at least 5.4 compared to the previous schemes.

In JPEG2000 standard, the number of bit planes of wavelet coefficients to be used in encoding is dependent on the compression ratio as well as subbands. These significant wavelet bit planes can be utilized to embed bits of secret data as they are retained in the final bit stream after Tier-2 encoding. In proposed techniques, the above mentioned concept have been utilized to embed secret data bits in lowest significant bit planes of the quantized wavelet coefficients of a cover image. In first technique, secret data is converted into a series of symbols using multiple bases notational system. These bases are selected by using the degree of local variation of coefficient values of the cover image so that coefficient of a complex region can potentially carry more secret data bits as compared to coefficients of smooth region. Symbols of secret data are embedded into bit planes of significant quantized wavelet coefficients by using EMD approaches. In second technique, the secret data bits are embedded into significant quantized wavelet coefficients by using modified EMD. Experimental results show that these proposed techniques provide large embedding capacity and better visual quality stego images than existing steganography techniques applicable to JPEG2000 compressed images. It has also been shown that modified EMD-based technique is better than EMD with multiple bases notational system (MBNS)-based technique.

In this paper, different types of image watermarking techniques, the embedding of data or copyright information into the data file, are investigated. Three image watermarking techniques are discussed, namely: least significant bit, least significant bit and discrete cosine transform combined, and discrete cosine transform and discrete wavelet transform combined. These embedded watermarking techniques are evaluated on how robust each technique is under image manipulations. Simulations are done using the three image watermarking techniques to determine the effects on how well the embedded watermarking technique resists manipulations. Different watermarking techniques resulted in high robustness in some cases but showed visible artefacts, in other cases robustness was low but image quality stayed relatively close to the original watermark.

Data Hiding is now a major area of study due to the internet’s and multimedia technologies’ amazing growth. Since data digitization and communication networking have advanced over the past ten years, protecting data transmitted over the internet has become a major concern. Numerous applications in steganography and watermarking find it desirable when data is integrated into multimedia cover content, such as audio, video, and photos. Watermarking will be used for copyright protection, while steganography will be chosen for encrypted communication. Even when the embedded data has been extracted, irreparable harm to the cover media is usually unavoidable with such techniques. The perfect restoration of the cover medium is necessary for some applications, including remote sensing, military mapping, geographic mapping, and medical diagnostics. Therefore, in sensitive applications like medical diagnosis, reversible data hiding techniques are used to restore the cover media without distortion. Confidential information, the content owner’s identity, cover content details, etc., are examples of the data that may be included. The data hiding techniques will be shown in order to determine the trade-off between embedding capacity and visual quality. The frequency coefficients of the cover image are changed by the frequency domain techniques. According to experimental results, the recommended procedures perform better than the current approaches for standard QCIF encoded videos and standard grayscale images utilizing the USC SIPI image database. The suggested method considers the information of the cover content during data embedding and provides a trade-off between visual quality and embedding capacity.

This paper proposes a steganography technique to hide secret messages in the least significant bits of the pixels of the cover image which are most different from their neighbourhood pixels. Since such pixels are the areas in an image which correspond to great changes in the visual property, they make a better option to hold secret data than smoother regions of the image, where a small distortion is much more noticeable. This paper uses LSB Matching algorithm for data embedding and the embedding method is adaptive to the amount of data in the message. Smaller is the amount of data, higher the value of threshold is chosen. The proposed technique is tested on BOWS2 Database consisting 10000 images and is compared with current steganography techniques for their robustness against various steganalysis methods. The proposed technique has given overall better results as compared to other techniques.

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

This paper used a robust mathematical way (binary coding method) to study shadow effect in photovoltaic arrays. Binary coding method provides a way to define power generation index (PGI) as a factor which shows the performance of arrays at shadow condition. Different configurations of photovoltaic (PV) array show different behavior at shadow condition. Configurations behavior depends on modules interconnections, bypass and blocking diodes, and etc. Configuration which has better working condition should be chosen for PV array. In this paper all conventional configurations are analyzed and compared by the use of value. Over currents which may create in some states of shadow is studied. Moreover, this paper deals with influence of working voltage range of inverter in maximum power point tracking. Finally, configurations are rated.

The transmission of image data acquired by remote sensing missions, based on space borne platforms is a major bottleneck, as a result of the limitation of on-board power, the huge volume of transmitted data, and the number of accessible ground receiving stations. In particular these arguments hold true for small satellites that faces additional design constraints in terms of size, mass and cost .To overcome downlink restriction, image compression has to be applied, although the provided data transmission rates are constantly growing, they can't keep up with the exponentially increasing data flood provided by the scanners, the reasons are twofold: First the acquisition rate exceeds the transmission rate. Second the satellite is not in constant visibility of ground receiving station, which effectively limits the downlinkable data volume per orbit. This paper introduces implementation of some of the compression techniques for both lossy and lossless which are used for the On-Board satellite missions, taking into consideration that the introduced compression method should support and enable the real time imaging and transmission. Also, a comparison study between both techniques is introduced based on measures like Compression Ratio (CR), Root Mean Square Error (RMSE) and Peak Signal-to-Noise Ratio (PSNR).The experimental results showed that: Huffman code is the most suitable code for lossless compression technique for satellite images, since it gives a considerable high compression ratio with respect to the other lossless algorithms (Run-Length Encode, Lempel-Ziv-Welch code and Arithmetic code). Huffman code does not require much storage capacity such as LZW or more computational requirements such as arithmetic code. Also, the most suitable lossy compression techniques for satellite images is applying Discrete Wavelet Transform (DWT) on the four Most Significant Bit Planes (MSPB) of the image then applying the arithmetic code over the resultant DWT coefficients. This technique achieves higher average compression ratio (8.28:1) than the two other techniques and at the same time the image quality is accepted.