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Nowadays, most image steganographic schemes embed secret messages by minimizing a well-designed distortion cost function for the corresponding domain, i.e., the spatial domain for spatial image steganography or the JPEG (Joint Photographic Experts Group) domain for JPEG image steganography. In this paper, we break the boundary between these two types of schemes by establishing a theoretical link between the distortion costs in the spatial domain and those in the JPEG domain and thus propose a scheme for domain transformations of distortion costs for efficient JPEG steganography with symmetric embedding, which can directly convert the spatial distortion cost into its JPEG counterpart. Specifically, by formulating the distortion cost function for JPEG images in the decompressed spatial domain, a closed-form expression for a distortion cost cross-domain transformation is derived theoretically, which precisely characterizes the conversion from the distortion costs obtained by existing spatial steganographic schemes to those applied in JPEG steganography. Experimental results demonstrate that the proposed method outperforms other advanced JPEG steganographic schemes, e.g., JUNIWARD (JPEG steganography with Universal Wavelet Relative Distortion), JMiPOD (JPEG steganography by Minimizing the Power of the Optimal Detector), and DCDT (Distortion Cost Domain Transformation), in resisting the detection of various advanced steganalyzers. [ABSTRACT FROM AUTHOR]

Today, as data is easily exposed through various channels, such as storing data in cloud services or exchanging data through a SNS (Social Network Service), related privacy issues are receiving a significant amount of attention. In addition, for data that are more sensitive to personal information, such as medical images, more attention should be paid to privacy protection. De-identification is a common method for privacy protection. Typically, it is a method of deleting or masking individual identifiers and omitting quasi-identifiers such as birth dates. In the case of images, de-identification is performed by mosaic processing or applying various effects. In this paper, we present a method of de-identifying an image by encrypting only some of the data in the JPEG (Joint Photograph Experts Group) image format, one of the most common image compression formats, so that the entire image cannot be recognized. The purpose of this paper is to protect images by encrypting only small parts, and not the entire image. This work is suitable for the fast and safe transmission and verification of high-capacity images. We have shown that images can be de-identified by encrypting data from the DHT (Define Huffman Table) segment among the JPEG header segments. Through experiments, we confirmed that that these images could not be identified after encrypting only a minimal portion, compared to previous studies that encrypted entire images, and the encryption speed and decryption speed were also faster and more effective than the results of previous studies. A model was implemented to de-identify images using AES-256 (Advanced Encryption Standard-256) and symmetric key encryption algorithm in the Huffman tables of JPEG headers, resulting in the ability to render entire images unidentifiable quickly and effectively. [ABSTRACT FROM AUTHOR]

With the development of digital media, its security has also been emphasized, and reversible data hiding (RDH) algorithms has been widely studied. This paper studied RDH algorithms for JPEG images, designed a method to embed secret information by frequency band selection based on discrete cosine transform (DCT) coefficients, called an improved RDH (IRDH) algorithm, and conducted experiments on the USC-SIPI image set. It was found that the designed RDH algorithm had a higher embedding capacity, with an average embedding capacity of 37 031 bits at quantization factor = 50, as well as a higher peak signal-to-noise ratio (PSNR) value and a lower file size increase (FSI) value, compared with the other methods; the dispersion degree of the data obtained by this algorithm was also low. The results demonstrate the reliability of the IRDH algorithm on JPEG images, which can be extended and applied in practice. [ABSTRACT FROM AUTHOR]

The JPEG format is widely used for its high compression rate in image storage.Privacy protection schemes applied to JPEG images not only need to safeguard the content of the privacy region but also maintain the file size.Furthermore, the region of interest (ROI), which contains private information, often occupies only a portion of the entire JPEG image.Protecting only the ROI can help preserve the file size.In light of this, an adaptable privacy protection scheme for JPEG images was proposed.Privacy regions were identified using methods like face detection within the JPEG images.These regions were then modified using the block-based adaptable reversible modification algorithm presented in this study.Reconstruction information was embedded into the image through reversible data hiding.The application of reversible algorithms in the privacy protection process enabled authorized users to fully restore the protected area.By introducing variable parameters, this scheme allowed for the selection of appropriate parameters to meet different practical requirements and achieve optimal encryption results.Additionally, the complex scenario of multiple overlapping ROIs was discussed and resolved.Experimental evaluations were conducted to investigate the influence of parameters on performance, considering both peak signal-to-noise ratio (PSNR) and file size increment.The results demonstrate that the proposed scheme outperforms existing schemes in terms of privacy protection and file size when suitable parameters are employed.

Copyright of Chinese Journal of Network & Information Security is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A reversible data hiding (RDH) in encrypted JPEG images (JPEG-RDH-EI) with an adaptive encryption key generated by minimum coded units histogram (MCUH) is proposed. However, the marked encrypted images are vulnerable to chosen-plaintext attack (CPA) since the MCUH is unchanged during the encryption and RDH process, which allows the encryption key can be reproduced by the marked encrypted image. To improve the security of marked encrypted images, this paper changes the MCUH in the RDH process by 0-1 conversion (refers to changing the value of coefficients from 0 to 1). To reduce the file growth, this paper explores the condition that the 0-1 conversion without file growth first. Then, a histogram shift scheme with embeddable zero coefficients is designed. The experimental results show that the proposed scheme can enhance the security of marked encrypted images by changing MCUH. In addition, the proposed algorithm has a smaller file growth and higher maximum embedding capacity than the existing histogram shift schemes since it embeds additional data in zero coefficients. [ABSTRACT FROM AUTHOR]

Joint photographic experts group (JPEG) images are widely used on the Internet due to their ability to maintain good picture quality while requiring less storage space.Reversible data hiding (RDH) techniques for JPEG images enable the hiding and extraction of secret information while allowing for lossless restoration of the original image.RDH is of great significance in file management and image authentication.However, many existing RDH methods result in a significant increase in the storage space of the encoded image after embedding secret information.For methods based on discrete cosine transform (DCT) coefficient embedding, the key issue that affects the performance of reversible information hiding in JPEG images is how to select the frequency band position.A reversible information hiding method for JPEG images was proposed, based on optimal DCT frequency embedding.The entropy decoded JPEG image was divided into 8×8 non-overlapping DCT blocks.The average texture complexity of each DCT block was calculated and ordered in ascending order.Then the alternating current (AC) in adjacent DCT blocks was paired pairwise.By satisfying the capacity of the information to be embedded, the optimal AC coefficient frequency position set was obtained from the distortion cost function of the AC coefficient frequency.The secret information was embedded according to the designed two-dimensional histogram mapping strategy.Experimental results demonstrate that the proposed method can reduce the expansion of the loaded image file’s storage size compared to existing methods, while maintaining good visual quality of the cover image.

Nowadays, most image steganographic schemes embed secret messages by minimizing a well-designed distortion cost function for the corresponding domain, i.e., the spatial domain for spatial image steganography or the JPEG (Joint Photographic Experts Group) domain for JPEG image steganography. In this paper, we break the boundary between these two types of schemes by establishing a theoretical link between the distortion costs in the spatial domain and those in the JPEG domain and thus propose a scheme for domain transformations of distortion costs for efficient JPEG steganography with symmetric embedding, which can directly convert the spatial distortion cost into its JPEG counterpart. Specifically, by formulating the distortion cost function for JPEG images in the decompressed spatial domain, a closed-form expression for a distortion cost cross-domain transformation is derived theoretically, which precisely characterizes the conversion from the distortion costs obtained by existing spatial steganographic schemes to those applied in JPEG steganography. Experimental results demonstrate that the proposed method outperforms other advanced JPEG steganographic schemes, e.g., JUNIWARD (JPEG steganography with Universal Wavelet Relative Distortion), JMiPOD (JPEG steganography by Minimizing the Power of the Optimal Detector), and DCDT (Distortion Cost Domain Transformation), in resisting the detection of various advanced steganalyzers.

Copyright of Chinese Journal of Network & Information Security is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Traditional image recovery from corrupted file systems plays a significant role in Digital Forensics investigation. The images are mainly considered objective court evidence. Since the JPEG image format is less structured than other image formats (e.g., BMP, PNG, GIF, and TIFF), its recovery is more challenging. The paper’s main objective is to apply a metaheuristic optimization algorithm with similarity metric to recover Bifragmented intertwined JPEG images. We propose a new method known as Meta-Heuristic Reassemble Images (MHRI) for forensic recovery of Bifragmented intertwined JPEG images in the scan area, where all the fragments are in a linear order. The contribution of this paper lies in the following key components composing the MHRI method: 1) restart marker to remove some strange blocks from the scan area; 2) coherence of Euclidean Distance metric (CoEDm) to detect the fragmentation point of intertwined JPEG image; and 3) genetic Algorithm with cost function to predict if every two blocks are sequenced in the same image that searches for the best reassembly solution among the existing solutions. The MHRI method is implemented using MATLAB and tested using public datasets of 25 JPEG images and private dataset of 6 JPEG images. The MHRI process can fully recover all the Bifragmented intertwined JPEG images and 48.4% of all the JPEG images, which comparably performs better than similar methods.

JPEG compression will cause severe distortion to the shared compressed image, which brings great challenges to extracting messages correctly from the stego image. To address such challenges, we propose a novel end-to-end robust data hiding scheme for JPEG images. The embedding and extracting secret messages on the quantized discrete cosine transform (DCT) coefficients are implemented by the bi-directional process of the invertible neural network (INN), which can provide intrinsic robustness against lossy JPEG compression. We design a JPEG compression attack module to simulate the JPEG compression process, which helps the network automatically learn how to recover the secret message from JPEG compressed image. Experimental results have demonstrated that our method achieves strong robustness against lossy JPEG compression, and also significantly improves the security compared with the existing data hiding methods on the premise of ensuring image quality and high capacity. For example, the detection error of our method against XuNet has been increased by 3.45% over the existing data hiding methods. • We propose a novel end-to-end robust data hiding scheme for JPEG images. • We design a JPEG compression attack module to simulate the JPEG compression process. • Our method achieves strong robustness against lossy JPEG compression. • Our method significantly improves security under high embedding capacity. [ABSTRACT FROM AUTHOR]

Most current JPEG steganalytic methods can only extract features from a series of linear residuals. Non-linear filters are not considered in these JPEG steganalytic methods, resulting in single types of residuals. Hence, a JPEG steganalytic method using non-linear residuals was proposed. Firstly, non-linear residuals were generated without a high computational cost by using element-wise minimum and maximum operations across a couple of linear residuals which had been obtained in the current JPEG steganalytic method. Secondly, according to the JPEG phase, the non-linear residual was divided into sub-residuals in which the histogram features were extracted. Thirdly, considering the minimum and maximum operators, the symmetrization method was accordingly designed. Finally, all the symmetrized histogram features were concatenated to form the final feature set. Experimental results indicate that the performance for JPEG steganalysis can be improved effectively by using both the linear and the non-linear residuals. [ABSTRACT FROM AUTHOR]

Recent research shows that the security performance of JPEG image steganography can be improved by developing an accurate statistical model to characterize the correlations between Discrete Cosine Transform (DCT) coefficients. In this paper, a novel JPEG steganographic scheme called J-CRF is proposed to characterize the correlations between DCT coefficients using a pairwise Conditional Random Field (CRF) model, in which the correlated DCT coefficient pairs are modeled as bivariate Gaussian random variables. Under the framework of pairwise CRF, the proposed scheme formulates the problem of minimizing the statistical detectability within the Gaussian image model as the minimization of the sum of a series of unary and pairwise potentials, both of which are utilized to measure the local detectability of embedding messages in the DCT coefficient pairs. All the potentials associated with statistical detectability are formalized as the KL divergence between the statistical distributions of the cover and the stego. Experimental results demonstrate that the proposed J-CRF can outperform other SOTA JPEG steganographic schemes, e.g., J-UNIWARD, J-MiPOD, and JEC-RL, in resisting the detection of various advanced steganalyzers. In addition, the performance of J-CRF could be further boosted by reformulating it as the weighted sum of unary and pairwise potentials, called J-CRFW. • Propose a novel JPEG steganographic scheme J-CRF using Conditional Random Field (CRF). • Characterize the correlations between DCT coefficients using pairwise CRF. • Cast the task of JPEG steganography as minimizing the detectability with CRF. • Improve J-CRF by reformulating the sum of potentials in a weighted manner. • Demonstrate superior security performance over other SOTA schemes. [ABSTRACT FROM AUTHOR]

Audio steganography (AS) uses the auditory redundancy of the human ear to conceal the hidden message inside the audio track. In recent studies, deep learning-based steganalysis has swiftly revealed AS by extracting high-dimensional stego acoustic features for categorization. There is still an opportunity for improvement in the current audio steganography required for managing communication confidentiality, access control and data protection. The main objective of this research is to improving the data protection by identifying the data embedding location in the audio. Generative Adversarial Network-based Audio Steganography Framework (GAN-ASF) is presented in this study, and it can automatically learn to provide better cover audio for message embedding. The suggested framework’s training architecture comprises a generator, a discriminator, and a steganalyzer learned using deep learning. The Least Significant Bit Matching (LSBM) message embedding technique encrypts the secret message into the steganographic cover audio, which is then forwarded to a trained steganalyzer for misinterpretation as cover audio. After performing the training, stenographic cover audio has been generated for encoding the secret message. Here, Markov model of co-frequency sub images to generate the best cover frequency sub-image to locate an image’s hidden payload. Steganographic cover audio created by GAN-ASF has been tested and found to be of excellent quality for embedding messages. The suggested method’s detection accuracy is lower than that of the most current state-of-the-art deep learning-based steganalysis. This payload placement approach has considerably increased stego locations’ accuracy in low frequencies. The test results GAN-ASF achieves a performance ratio of 94.5 %, accuracy ratio of 96.2 %, an error rate of 15.7 %, SNR 24.3 %, and an efficiency ratio of 94.8 % compared to other methods [ABSTRACT FROM AUTHOR]

Due to the advancement of a variety of photo editing and image processing software, image forensics analysis has become an important research topic in recent years. Numbers of research works are presented for image forensic analysis. Accordingly, this paper proposes a method named as Dragonfly Bayes Fusion System (DBFS) by integrating the Naive Bayes (NB) classifier and the Dragonfly optimization for detecting the tampered Joint Photographic Experts Group image. Initially, the input image is applied to the existing six forensic tools separately, and the classified binary map is generated. Then, the proposed DBFS fuses these decisions for generating the optimal decision. Here, the NB classifier creates the model by finding the mean and variance of every feature and this model is given as input to the Dragonfly optimization for optimally generating the probabilistic measures. Finally, the posterior probability of each feature is determined with respect to the tampered class, and the original class and the tampered image block is determined. The performance of the proposed system is evaluated with the existing methods, such as fuzzy theory based classification, rule-based classification, average method, and weighted average method for the evaluation metrics accuracy, False Positive Rate (FPR), and True Positive Rate (TPR). The experimental results show that the proposed system outperforms the existing methods by obtaining the maximum accuracy of 0.9519, minimum FPR of 0.0490, and maximum TPR of 0.8720 when compared to the existing methods. [ABSTRACT FROM AUTHOR]

Robust reversible watermarking (RRW) is a potential technology for copyright protection and integrity authentication due to its ability in both robustness and reversibility. Currently, there is no detailed report on RRW of JPEG images. In this paper, we propose an RRW algorithm of JPEG images by selecting quantized discrete cosine transform coefficients to construct robust features for watermarking. In the proposed algorithm, a watermark sequence can be embedded into a JPEG image by shifting the histogram of its constructed robust features. For less embedding distortion, smaller file size, and higher structural similarity, an evaluation method has been designed to select those appropriate frequency bands for watermarking. On the receiver side, the watermark can be accurately extracted by reconstructing the robust features, and the original JPEG image can be restored losslessly by performing the inverse operation of the histogram shifting. Experimental results show that the watermark is robust to common image processing operations (e.g., JPEG recompression, JPEG2000 compression, WebP compression, and additive white Gaussian noise), and can effectively resist those attacks from the lossy channels in real life, such as the most popular apps Instagram and WeChat. • Propose a robust reversible watermarking algorithm of JPEG images. • Propose a method to construct robust features in JPEG images. • Design an evaluation method to select appropriate frequency bands for watermarking. • The proposed algorithm achieves reversibility for JPEG images and strong robustness. [ABSTRACT FROM AUTHOR]

Abstract The excellent cover estimation is very important to the payload location of JPEG image steganography. But it is still hard to exactly estimate the quantized DCT coefficients in cover JPEG image. Therefore, this paper proposes a JPEG image steganography payload location method based on optimal estimation of cover co-frequency sub-image, which estimates the cover JPEG image based on the Markov model of co-frequency sub-image. The proposed method combines the coefficients of the same position in each 8 × 8 block in the JPEG image to obtain 64 co-frequency sub-images and then uses the maximum a posterior (MAP) probability algorithm to find the optimal estimations of cover co-frequency sub-images by the Markov model. Then, the residual of each DCT coefficient is obtained by computing the absolute difference between it and the estimated cover version of it, and the average residual over coefficients in the same position of multiple stego images embedded along the same path is used to estimate the stego position. The experimental results show that the proposed payload location method can significantly improve the locating accuracy of the stego positions in low frequencies.

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a commonly used image format, JPEG image is popularly used as the carrier for data hiding. After analyzing the virtue of the exploiting-modification-direction (EMD) scheme, which is designed for the spatial domain, this paper reforms its extraction function and applies it to the non-zero alternating current (AC) coefficients of JPEG images. Besides, a block and coefficient selection strategy is utilised to further improve the image quality and suppress the increase of file size. More specifically, the smooth discrete cosine transform (DCT) blocks with fewer zero AC coefficients are preferentially selected to embed data. The experiments indicate that our scheme achieves a high embedding capacity, meanwhile, the stego-image quality keeps good and the file size preserves well, moreover, our scheme is superior to the state-of-the-art scheme. [ABSTRACT FROM AUTHOR]

Most current reversible data hiding (RDH) techniques are designed for uncompressed images. However, JPEG images are more commonly used in our daily lives. Up to now, several RDH methods for JPEG images have been proposed, yet few of them investigated the adaptive data embedding as the lack of accurate measurement for the embedding distortion. To realize adaptive embedding and optimize the embedding performance, in this article, a novel RDH scheme for JPEG images based on multiple histogram modification (MHM) and rate-distortion optimization is proposed. Firstly, with selected coefficients, the RDH for JPEG images is generalized into a MHM embedding framework. Then, by estimating the embedding distortion, the rate-distortion model is formulated, so that the expansion bins can be adaptively determined for different histograms and images. Finally, to optimize the embedding performance in real time, a greedy algorithm with low computation complexity is proposed to derive the nearly optimal embedding efficiently. Experiments show that the proposed method can yield better embedding performance compared with state-of-the-art methods in terms of both visual quality and file size preservation. [ABSTRACT FROM AUTHOR]

Because of the raising needs for transmitting images in computer, mobile milieus, the study in the area of compressing image maximized considerably. Compressing image plays a critical part in processing digital images. The essential concept of compressing data is to decrease the data correlation. Through employing Discrete Cosine Transform (DCT), the data in time field could be transmuted into the field of frequency. Due to the reduced sensitivity of human sight in higher frequency, I is possible to compress data of the image or video by overturning its high frequency constituents nonetheless do no alteration to the eye. When pictures move like in video, the data in three-dimnsional space includes spatial plane and time axis. Hence, beside decreasing spatial correlation, time correlation is needed to be decreased. A process is presented named Motion Estimation (ME). Moreover, we can substitute the image by a Motion Vector (MV) to decrease time correlation. Thus, the improvement of effective methods for image compression becomes essential. Through the study, we similarly present JPEG standard and MPEG standard that are reputed image and video compression standard, correspondingly. [ABSTRACT FROM AUTHOR]

• Novel block sorting method. In this paper, the smoothness of the block is evaluated by using the number of zeros in the EOB and the sum of squares of the differences between the DC (Direct current, DC) coefficients of the block and the four neighborhoods of the context. • Segmented data embedding. The sequence of blocks is divided into three segments. The first and second segments expand peak points (−1, 1) and (−1, 0) to embed data, respectively. The blocks in the third segment are kept unchanged. • Dynamic allocation solution method. The approximate optimal segmentation of the DCT block sequence can be quickly solved by the dynamic allocation solution method. This method reduces the solution space by setting the dynamic allocation step size. Existing JPEG image reversible data hiding (RDH) schemes based on quantized DCT (Discrete cosine transform) modification usually use non-zero or zero AC (Alternating current) coefficients as peak points for data embedding. However, this approach tends to limit the embedding capacity or result in significant file size growth. This paper proposed an RDH scheme for JPEG images based on DCT block sorting and segmented embedding. This scheme can take into account the dual advantages of having a non-zero or zero AC coefficient as the peak point, so it has both high embedding capacity and low file growth, and good visual quality. Firstly, a new DCT block sorting method is designed, the smoothness of the block is estimated by the number of zero coefficients in the EOB (End of Block) and the fluctuation of the DC coefficient in the block, and the zero coefficients in the EOB in the block have not embedded data. Then, the sorted DCT block sequence is divided into three segments, the peak points of the front two segments are (−1, 1) and (−1, 0) respectively, and the third segment may be empty but it always remains unchanged. Finally, the dynamic allocation method is used to quickly solve the optimal segmentation point to achieve the optimal embedding performance. The experimental results show that the overall performance of this scheme is better than the existing state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Inter-block shuffle has been proved to be able to enhance the security for JPEG image encryption. However, it does not change the numbers of non-zero coefficients in 8*8 blocks. This leads to information leakage. In this paper, the defects of inter-block shuffle are analyzed. An attack scheme is developed based on a combined application of chosen-plain-text attack and non-zero quantized coefficients counting attack. It is verified that the main content of the original image could be reconstructed without the knowledge of encryption algorithm details and keys. The attack results are visualized to be mosaic appearance images. An improvement of the attack is also provided, which is called a fast mosaic attack. In the improved attack, the chosen images are designed to have distinguished numbers of non-zero quantized DCT coefficients in different blocks. The designed images remarkably accelerate the attack processing. The fast mosaic attack generates the same results as the original scheme with the much smaller time cost.

The excellent cover estimation is very important to the payload location of JPEG image steganography. But it is still hard to exactly estimate the quantized DCT coefficients in cover JPEG image. Therefore, this paper proposes a JPEG image steganography payload location method based on optimal estimation of cover co-frequency sub-image, which estimates the cover JPEG image based on the Markov model of co-frequency sub-image. The proposed method combines the coefficients of the same position in each 8 × 8 block in the JPEG image to obtain 64 co-frequency sub-images and then uses the maximum a posterior (MAP) probability algorithm to find the optimal estimations of cover co-frequency sub-images by the Markov model. Then, the residual of each DCT coefficient is obtained by computing the absolute difference between it and the estimated cover version of it, and the average residual over coefficients in the same position of multiple stego images embedded along the same path is used to estimate the stego position. The experimental results show that the proposed payload location method can significantly improve the locating accuracy of the stego positions in low frequencies. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) can be used to imperceptibly embed data into images in a reversible manner. Many RDH schemes have been developed for uncompressed images. However, JPEG compressed images are more widely used in our daily lives. The existing RDH techniques for JPEG images may cause significant distortion or a large increase in the file size of marked images. In this paper, a novel RDH scheme for JPEG images is proposed. First, the negative influence models of data embedding, including image visual distortion model and file size change model, are mathematically established. Then, a negative index for each frequency is defined as the weighted sum of the normalized average image visual distortion and the normalized average file size change per 1-bit hidden data, and the frequencies with small negative indices will be used for data embedding with a high priority. The weighting factor can be adjusted according to the user’s preference for less image distortion or smaller file size. Lastly, secret data is embedded into non-zero quantized AC coefficients of the selected frequencies in ascending order of zero-run length. Extensive experiments conducted on typical images and a well-known image database show that the presented negative influence models are effective, and the proposed RDH scheme based on the models can achieve low image distortion and small increase in the file size of marked images. [ABSTRACT FROM AUTHOR]

Manipulating digital images is not often a difficult task due to the rapid development of software and image manipulation techniques. Hence, there is no need for professional skills or training. When used as an artistic tool, it is completely harmless, but when these images can be presented in judicial system as evidence or for the creation of political associations, as well as, using them in legal documents, electronic money circulation or press; in these cases, the distinction between an original image and a forgery image is very important. In order to solve the problem in this research using a Discrete Wavelet Transform (DWT), which is performed by decomposing a signal into smaller and smaller details, as well as, the use of periodic patterns in the histogram generated by double compression with different coefficients, significant improvements were made in terms of reducing computations and increasing the detection rate of forging areas. Many of the proposed methods for detecting image forgery use a feature extraction model from a valid and manipulated dataset and then classify them using machine learning with the aim of optimizing the accuracy. In this research, following the extraction of features in the proposed method, using the SVM classification identifies image forgery and then identifies the forging area after it detects the falsification or originality of the image. The results of this study indicate 97.98% accuracy in the Columbia database and 98.1% in the IFS-TC database. [ABSTRACT FROM AUTHOR]

• Design a block difference model to select similar DCT blocks by combining the metrics of texture, location, and template matching. • Number of similar DCT blocks involved in Laplacian distribution estimation is selected adaptively. • Block difference threshold and the distance threshold are set further to improve the accuracy of AC coefficient distribution estimation. [Display omitted] Reversible data hiding (RDH) for JPEG images has attracted extensive attentions in recent years. As far, a number of related schemes have been proposed, which enhance the embedding performance by improving the strategies such as frequency selection and block sorting to choose appropriate embedding coefficients with the histogram shifting mechanism. Nevertheless, the existing methods do not fully consider the characteristics of DCT coefficients and lack accurate measurement on the embedding distortion. To address the above problems, we propose an improved general framework of RDH for JPEG images based on the Laplacian distribution model. The block difference model is first established for the alternating current (AC) coefficients fitting. Subsequently, the scale parameter is calculated to estimate the embedding efficiency of each AC coefficient, and the coefficients with high embedding efficiency are preferentially selected for embedding. Furthermore, the proposed framework can be combined with other JPEG RDH methods based on quantized DCT coefficient modification. Experimental results demonstrate that better performance in terms of both visual quality and file size preservation can be achieved with the proposed scheme compared with the state-of-the-art RDH schemes for JPEG images. [ABSTRACT FROM AUTHOR]

In order to solve the problem of embedding capacity, imperceptibility, real-time and tampering localization in JPEG image watermarking algorithm, this paper proposed a JPEG watermarking algorithm based on entropy coding. Firstly, the algo¬rithm located the process of JPEG entropy coding to embed the watermarking, which could avoid the forward and reverse quantization operations and ensured that during embedding image changes was small and had good real-time performance. Se¬condly, according to the principle that some hits in the entropy coding process do not participate in the Huffman coding, the algorithm chose appropriate coefficient to embed watermark. This algorithm embedded watermarking information into the least significant hits of these coefficients to avoid the coding error caused by the modification of the Huffman coding coefficient, which should further enhance the imperceptibility of the algorithm. Experimental results show that the algorithm not only has a large embedded capacity and good imperceptibility, hut also has high fragility and can accurately locate malicious tampering. [ABSTRACT FROM AUTHOR]