A Recursive High Payload Reversible Data Hiding Using Integer Wavelet and Arnold Transform

Reversible data hiding is an information hiding technique that requires the retrieval of the error free cover image after the extraction of the secret image.We suggested a technique in this research that uses a recursive embedding method to increase capacity substantially using the Integer wavelet transform and the Arnold transform.The notion of Integer wavelet transforms is to ensure that all coefficients of the cover images are used during embedding with an increase in payload.By scrambling the cover image,Arnold transform adds security to the information that gets embedded and also allows embedding more information in each iteration.The hybrid combination of Integer wavelet transform and Arnold transform results to build a more efficient and secure system.The proposed method employs a set of keys to ensure that information cannot be decoded by an attacker.The experimental results show that it aids in the development of a more secure storage system and withstand few tampering attacks The suggested technique is tested on many image formats,including medical images.Various performance metrics proves that the retrieved cover image and hidden image are both intact.This System is proven to withstand rotation attack as well.

Improved Dual-image Quality with Reversible Data Hiding Using Translocation and Switching Strategy

Dual-image reversible data hiding(RDH)is a technique for hiding important messages.This technology can be used to safely deliver secret mes-sages to the recipient through dual images in an open network without being easily noticed.The recipient of the image must receive the two stego-images before the secret message can be completely retrieved.Imperceptibility is one of the main advantages of data hiding technology;to increase the imperceptibility,the quality requirements of the stego-images are relatively important.A dual ste-ganographic image RDH method,called a DS-CF scheme that can achieve a bet-ter steganographic image quality using the center folding(CF)strategy.In this paper,we developed a translocation and switching strategy(TaS)to shorten the distances between the stego-pixel coordinates and the cover pixel coordinates after information being hidden.Compared with the DS-CF scheme,our proposed DS-TaS scheme can effectively improve the quality of the steganographic images at the same level of embedding capability.The experimental results show that the PSNR of our DS-TaS scheme at k=1 was 55.66 dB,which is an increase of 1.5 dB,and is 51.43 dB for k=2,46.66 dB for k=3,and 40.91 dB for k=4.In addition,the PSNR values of the stego images was increased by 1.5,0.29,0.29,and 0.19 dB,respectively.This shows that our proposed dual-image RDH method can optimize the visual quality of the stego-images and is better than many other dual-image RDH techniques.

On the Privacy-Preserving Outsourcing Scheme of Reversible Data Hiding over Encrypted Image Data in Cloud Computing

Advanced cloud computing technology provides cost saving and flexibility of services for users.With the explosion of multimedia data,more and more data owners would outsource their personal multimedia data on the cloud.In the meantime,some computationally expensive tasks are also undertaken by cloud servers.However,the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data.Recently,this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data.In this paper,two reversible data hiding schemes are proposed for encrypted image data in cloud computing:reversible data hiding by homomorphic encryption and reversible data hiding in encrypted domain.The former is that additional bits are extracted after decryption and the latter is that extracted before decryption.Meanwhile,a combined scheme is also designed.This paper proposes the privacy-preserving outsourcing scheme of reversible data hiding over encrypted image data in cloud computing,which not only ensures multimedia data security without relying on the trustworthiness of cloud servers,but also guarantees that reversible data hiding can be operated over encrypted images at the different stages.Theoretical analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed scheme.The computation cost of the proposed scheme is acceptable and adjusts to different security levels.

Reversible Data Hiding in Encrypted Image Based on Block Classification Permutation

Recently,reversible data hiding in encrypted image(RDHEI)has attracted extensive attention,which can be used in secure cloud computing and privacy protection effectively.In this paper,a novel RDHEI scheme based on block classification and permutation is proposed.Content owner first divides original image into non-overlapping blocks and then set a threshold to classify these blocks into smooth and non-smooth blocks respectively.After block classification,content owner utilizes a specific encryption method,including stream cipher encryption and block permutation to protect image content securely.For the encrypted image,data hider embeds additional secret information in the most significant bits(MSB)of the encrypted pixels in smooth blocks and the final marked image can be obtained.At the receiver side,secret data will be extracted correctly with data-hiding key.When receiver only has encryption key,after stream cipher decryption,block scrambling decryption and MSB error prediction with threshold,decrypted image will be achieved.When data hiding key and encryption key are both obtained,receiver can find the smooth and non-smooth blocks correctly and MSB in smooth blocks will be predicted correctly,hence,receiver can recover marked image losslessly.Experimental results demonstrate that our scheme can achieve better rate-distortion performance than some of state-of-the-art schemes.

Local binary pattern-based reversible data hiding

A novel local binary pattern-based reversible data hiding(LBP-RDH)technique has been suggested to maintain a fair symmetry between the perceptual transparency and hiding capacity.During embedding,the image is divided into various 3×3 blocks.Then,using the LBP-based image descriptor,the LBP codes for each block are computed.Next,the obtained LBP codes are XORed with the embedding bits and are concealed in the respective blocks using the proposed pixel readjustment process.Further,each cover image(CI)pixel produces two different stego-image pixels.Likewise,during extraction,the CI pixels are restored without the loss of a single bit of information.The outcome of the proposed technique with respect to perceptual transparency measures,such as peak signal-to-noise ratio and structural similarity index,is found to be superior to that of some of the recent and state-of-the-art techniques.In addition,the proposed technique has shown excellent resilience to various stego-attacks,such as pixel difference histogram as well as regular and singular analysis.Besides,the out-off boundary pixel problem,which endures in most of the contemporary data hiding techniques,has been successfully addressed.

An Effective Steganalysis Algorithm for Histogram-Shifting Based Reversible Data Hiding

To measure the security for hot searched reversible data hiding(RDH)technique,especially for the common-used histogram-shifting based RDH(denoted as HS-RDH),several steganalysis schemes are designed to detect whether some secret data has been hidden in a normal-looking image.However,conventional steganalysis schemes focused on the previous RDH algorithms,i.e.,some early spatial/pixel domain-based histogram-shifting(HS)schemes,which might cause great changes in statistical characteristics and thus be easy to be detected.For recent improved methods,such as some adaptive prediction error(PE)based embedding schemes,those conventional schemes might be invalid,since those adaptive embedding mechanism would effectively reduce the embedding trace and thus increase the difficulty of steganalysis.Therefore,a novel steganalysis method is proposed in this paper to detect recent adaptive RDH schemes and provide a more effective detection tool for RDH.The contributions of this paper could be summarized as follows.(1)By analyzing the characteristics for those adaptive HS-RDH,an effective“flat ground”based detection method is designed to fast identify whether the given image is used to hide secret data;(2)According to the empirical statistical model,double check mechanism is provided to improve the detection accuracy;(3)In addition,to further improve detection ability,some detailed information for secret data,i.e.,its content and embedding location are further estimated.Compared with conventional steganalysis methods,experimental results indicate that our proposed algorithm could achieve a better detection accuracy and meanwhile acquire more detailed information on secret data.

Reversible Data Hiding in Encrypted Images Based on Prediction and Adaptive Classification Scrambling

Reversible data hiding in encrypted images(RDH-EI)technology is widely used in cloud storage for image privacy protection.In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images,we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling.First,the prediction error image is obtained by a novel prediction method before encryption.Then,the image pixel values are divided into two categories by the threshold range,which is selected adaptively according to the image content.Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged.The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm.Moreover,the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position.Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-of-the-art methods for images with different texture complexity.

Reversible Data Hiding Based on Pixel-Value-Ordering and Pixel Block Merging Strategy

With the reversible data hiding method based on pixel-value-ordering,data are embedded through the modification of the maximum and minimum values of a block.A significant relationship exists between the embedding performance and the block size.Traditional pixel-value-ordering methods utilize pixel blocks with a fixed size to embed data;the smaller the pixel blocks,greater is the embedding capacity.However,it tends to result in the deterioration of the quality of the marked image.Herein,a novel reversible data hiding method is proposed by incorporating a block merging strategy into Li et al.’s pixel-value-ordering method,which realizes the dynamic control of block size by considering the image texture.First,the cover image is divided into non-overlapping 2×2 pixel blocks.Subsequently,according to their complexity,similarity and thresholds,these blocks are employed for data embedding through the pixel-value-ordering method directly or after being emerged into 2×4,4×2,or 4×4 sized blocks.Hence,smaller blocks can be used in the smooth region to create a high embedding capacity and larger blocks in the texture region to maintain a high peak signal-to-noise ratio.Experimental results prove that the proposed method is superior to the other three advanced methods.It achieves a high embedding capacity while maintaining low distortion and improves the embedding performance of the pixel-value-ordering algorithm.

Reversible Data Hiding in Classification-Scrambling Encrypted-Image Based on Iterative Recovery

To improve the security and quality of decrypted images,this work proposes a reversible data hiding in encrypted image based on iterative recovery.The encrypted image is firstly generated by the pixel classification scrambling and bit-wise exclusive-OR(XOR),which improves the security of encrypted images.And then,a pixel-typemark generation method based on block-compression is designed to reduce the extra burden of key management and transfer.At last,an iterative recovery strategy is proposed to optimize the marked decrypted image,which allows the original image to be obtained only using the encryption key.The proposed reversible data hiding scheme in encrypted image is not vulnerable to the ciphertext-only attack due to the fact that the XOR-encrypted pixels are scrambled in the corresponding encrypted image.Experimental results demonstrate that the decrypted images obtained by the proposed method are the same as the original ones,and the maximum embedding rate of proposed method is higher than the previously reported reversible data hiding methods in encrypted image.

A Reversible Data Hiding Algorithm Based on Image Camouflage and Bit-Plane Compression

Reversible data hiding in encrypted image(RDHEI)is a widely used technique for privacy protection,which has been developed in many applications that require high confidentiality,authentication and integrity.Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image.Moreover,the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers.This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression.A camouflage encryption algorithm is used to transform a secret image into another meaningful target image,which can cover both secret image and encryption behavior based on“plaintext to plaintext”transformation.An edge optimization method based on prediction algorithm is designed to improve the image camouflage encryption quality.The reversible data hiding based bit-plane level compression,which can improve the redundancy of the bit plane by Gray coding,is used to embed watermark in the camouflage image.The experimental results also show the superior performance of the method in terms of embedding capacity and image quality.

Reversible Data Hiding for Medical Images in Cloud Computing Environments Based on Chaotic Hénon Map

Reversible data hiding techniques are capable of reconstructing the original cover image from stego-images. Recently, many researchers have focused on reversible data hiding to protect intellectual property rights. In this paper, we combine reversible data hiding with the chaotic Henon map as an encryption technique to achieve an acceptable level of confidentiality in cloud computing environments. And, Haar digital wavelet transformation （HDWT） is also applied to convert an image from a spatial domain into a frequency domain. And then the decimal of coefficients and integer of high frequency band are modified for hiding secret bits. Finally, the modified coefficients are inversely transformed to stego-images.

Reversible Data Hiding in Encrypted Images Based on Adaptive Prediction and Labeling

Recently,reversible data hiding in encrypted images(RDHEI)based on pixel prediction has been a hot topic.However,existing schemes still employ a pixel predictor that ignores pixel changes in the diagonal direction during prediction,and the pixel labeling scheme is inflexible.To solve these problems,this paper proposes reversible data hiding in encrypted images based on adaptive prediction and labeling.First,we design an adaptive gradient prediction(AGP),which uses eight adjacent pixels and combines four scanning methods(i.e.,horizontal,vertical,diagonal,and diagonal)for prediction.AGP can adaptively adjust the weight of the linear prediction model according to the weight of the edge attribute of the pixel,which improves the prediction ability of the predictor for complex images.At the same time,we adopt an adaptive huffman coding labeling scheme,which can adaptively generate huffman codes for labeling according to different images,effectively improving the scheme’s embedding performance on the dataset.The experimental results show that the algorithm has a higher embedding rate.The embedding rate on the test image Jetplane is 4.2102 bpp,and the average embedding rate on the image dataset Bossbase is 3.8625 bpp.

A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

This paper proposes a two-step general framework for reversible data hiding(RDH)schemes with controllable contrast enhancement.The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity(EC),while the second step is used for increasing image contrast.In the second step,some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization(HE),which would lead to the image contrast enhancement.However,for HE,the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded.Therefore,in our proposed framework,contrast over-enhancement is avoided by controlling the degree of contrast enhancement.Since the second step can only provide a small amount of data due to controlled contrast enhancement,the first one helps to achieve a large amount of data without degrading visual quality.Any RDH method which can achieve high EC while preserve good visual quality,can be selected for the first step.In fact,Gao et al.’s method is a special case of our proposed framework.In addition,two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.

Reversible Data Embedding Scheme Using Relationships between Pixel-Values and Their Neighbors

Reversible data embedding is becoming a very important issue in securing images transmitted over the Internet, especially in dealing with sensitive images such as those created for military data and medical data. Based on the relationships between pixels and their neighbors, we propose a reversible data embedding scheme to embed hidden messages into an original image. In our proposed scheme, a two-layer data embedding approach is used for our proposed data embedding phase. Layer-1 embedding is used to hide secret data. Layer-2 embedding, which is an embedding variant of the proposed layer-1 embedding, is used to hide side information, such as the parameters required to restore the marked image. In our layer-1 embedding, the value of an embedded pixel is determined according to a predetermined threshold and the relationship between the pixel and its neighbors. In our layer-2 embedding, the similar data embedding concept is expanded to the block-based. Experimental results provide supportive data to show that the proposed scheme can provide greater hiding capacity while preserving the image quality of a marked image in comparison with previous work.

Reversible Data Hiding Based on Run-Level Coding in H.264/AVC Video Streams

This paper presents a reversible data hiding(RDH)method,which is designed by combining histogram modification(HM)with run-level coding in H.264/advanced video coding(AVC).In this scheme,the run-level is changed for embedding data into H.264/AVC video sequences.In order to guarantee the reversibility of the proposed scheme,the last nonzero quantized discrete cosine transform(DCT)coefficients in embeddable 4×4 blocks are shifted by the technology of histogram modification.The proposed scheme is realized after quantization and before entropy coding of H.264/AVC compression standard.Therefore,the embedded information can be correctly extracted at the decoding side.Peak-signal-noise-to-ratio(PSNR)and Structure similarity index(SSIM),embedding payload and bit-rate variation are exploited to measure the performance of the proposed scheme.Experimental results have shown that the proposed scheme leads to less SSIM variation and bit-rate increase.

Reversible Data Hiding Based on Greedy Pairing Prediction-Error Expansion

Reversible data hiding(RDH)is a method to embed messages into an image that human eyes are difficult to recognize the differences between the original image and the embedded image.The method needs to make sure that the original image and the embedded information can be exactly recovered.The prediction-error expansion(PEE)is a successful way to realize RDH.However,it is fixed when pairing the conventional twodimensional prediction-error histogram(2D-PEH).So,the embedding capacity(EC)and embedding distortion(ED)are not satisfactory.In this study,we propose a method called greedy pairing prediction-error expansion(GPPEE)based on pairwise RDH and demonstrate GPPEE can achieve a more efficient embedding goal and reduce ED.

A Steganography Based on Optimal Multi-Threshold Block Labeling

Hiding secret data in digital images is one of the major researchfields in information security.Recently,reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services.This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique(OMTBL-RDHEI).In our scheme,the content owner encrypts the cover image with block permutation,pixel permutation,and stream cipher,which preserve the in-block correlation of pixel values.After uploading to the cloud service,the data hider applies the prediction error rearrangement(PER),the optimal threshold selection(OTS),and the multi-threshold labeling(MTL)methods to obtain a compressed version of the encrypted image and embed secret data into the vacated room.The receiver can extract the secret,restore the cover image,or do both according to his/her granted authority.The proposed MTL labels blocks of the encrypted image with a list of threshold values which is optimized with OTS based on the features of the current image.Experimental results show that labeling image blocks with the optimized threshold list can efficiently enlarge the amount of vacated room and thus improve the embedding capacity of an encrypted cover image.Security level of the proposed scheme is analyzed and the embedding capacity is compared with state-of-the-art schemes.Both are concluded with satisfactory performance.

Study of Difference-Expansion Embedding Schemes

Difference expansion（DE） is one of the famous schemes in the field of reversible data hiding.With the high efficiency and simplicity,DE also has received more attention over the years.DE has a good information capacity,but due to its major location map,the pure payload is rather low.Therefore many scholars did relevant improvements which let n pixels as a unit instead of the original two pixels as a unit and can adaptively adjust the number of embedding secret information according to the smoothness degree of the block,which achieves the result of improving the information payload or the image quality.In this paper,the study of DE-based reversible data hiding schemes is comprehensively discussed.The performance of DEbased schemes is evaluated and compared in terms of embedding capacity and stego-image quality.

A Block Mean Insertion and Dual Stego Generation Based Embedding Strategy

In reversible data hiding, pixel value ordering is an up-to-the-minute research idea in the field of data hiding. Secret messages are embedded in the maximum or the minimum value among the pixels in a block. Pixel value ordering helps identify the embeddable pixels in a block but suffers from fewer embedding payloads. It leaves many pixels in a block without implanting any bits there. The proposed scheme in this paper resolved that problem by allowing every pixel to conceive data bits. The method partitioned the image pixels in blocks of size two. In each block, it first orders these two pixels and then measures the average value. The average value is placed in the middle of these two pixels. Thus, the scheme extends the block size from two to three. After applying the embedding method of Weng et al., the implantation task removed the average value from the block to reduce its size again to two. These two alive pixels are called stego pixels, which produced a stego image. A piece of state information is produced during implanting to track whether a change is happening to the block’s cover pixels. This way, after embedding in all blocks, a binary stream of state information is produced, which has later been converted to decimal values. Thus, image data were assembled in a two-dimensional array. Considering the array as another image plane, Weng et al.’s method is again applied to embed further to produce another stego image. Model validation ensured that the proposed method performed better than previous work in this field.

Reversible data hiding using a transformer predictor and an adaptive embedding strategy

In the field of reversible data hiding(RDH),designing a high-precision predictor to reduce the embedding distortion and developing an effective embedding strategy to minimize the distortion caused by embedding information are the two most critical aspects.In this paper,we propose a new RDH method,including a predictor based on a transformer and a novel embedding strategy with multiple embedding rules.In the predictor part,we first design a transformer-based predictor.Then,we propose an image division method to divide the image into four parts,which can use more pixels as context.Compared with other predictors,the transformer-based predictor can extend the range of pixels for prediction from neighboring pixels to global ones,making it more accurate in reducing the embedding distortion.In the embedding strategy part,we first propose a complexity measurement with pixels in the target blocks.Then,we develop an improved prediction error ordering rule.Finally,we provide an embedding strategy including multiple embedding rules for the first time.The proposed RDH method can effectively reduce the distortion and provide satisfactory results in improving the visual quality of data-hidden images,and experimental results show that the performance of our RDH method is leading the field.