High-Capacity Framework for Reversible Data Hiding in Encrypted Image Using Pixel Predictions and Entropy Encoding

Previous reversible data hiding in encrypted images (RDHEI) schemes can be either carried out by vacating room before or after data encryption, which leads to a separation of the search field in RDHEI. Besides, high capacity relies heavily on vacating room before encryption (VRBE), which significantly lowers the payload of vacating room after encryption (VRAE) based schemes. To address this issue, this paper proposes a framework for high-capacity RDHEI for both VRBE and VRAE cases using pixel predictions and entropy encoding. We propose an embedding room generation algorithm to produce vacated room by generating the prediction-error histogram (PEH) of the selected cover using adjacency prediction and the median edge detector (MED). In the VRBE scenario, we propose a scheme that generates the embedding room using the proposed algorithm, and encrypts the preprocessed image by using the stream cipher with two encryption keys. In the VRAE scenario, we propose a scheme that involves an improved block modulation and permutation encryption algorithm where the spatial redundancy in the plain-text image can be largely preserved. Then the proposed algorithm is applied on the encrypted image to generate the embedding room. At the data hider's side of both the schemes, the data hider locates the embedding room and embeds the encrypted additional data. On receiving the marked encrypted image, the receivers with different authentication can respectively conduct error-free data extraction and/or error-free image recovery. The experimental results show that the two schemes in the proposed framework can outperform many previous state-of-the-art RDHEI arts. Besides, the proposed schemes can ensure high information security in that little detail of the original image can be directly discovered from the encrypted images or the marked encrypted images

Fully Homomorphic Encryption Encapsulated Difference Expansion for Reversible Data hiding in Encrypted Domain

This paper proposes a fully homomorphic encryption encapsulated difference expansion (FHEE-DE) scheme for reversible data hiding in encrypted domain (RDH-ED). In the proposed scheme, we use key-switching and bootstrapping techniques to control the ciphertext extension and decryption failure. To realize the data extraction directly from the encrypted domain without the private key, a key-switching based least-significant-bit (KS-LSB) data hiding method has been designed. In application, the user first encrypts the plaintext and uploads ciphertext to the server. Then the server performs data hiding by FHEE-DE and KS-LSB to obtain the marked ciphertext. Additional data can be extracted directly from the marked ciphertext by the server without the private key. The user can decrypt the marked ciphertext to obtain the marked plaintext. Then additional data or plaintext can be obtained from the marked plaintext by using the standard DE extraction or recovery. A fidelity constraint of DE is introduced to reduce the distortion of the marked plaintext. FHEE-DE enables the server to implement FHEE-DE recovery or extraction on the marked ciphertext, which returns the ciphertext of original plaintext or additional data to the user. In addition, we simplified the homomorphic operations of the proposed universal FHEE-DE to obtain an efficient version. The Experimental results demonstrate that the embedding capacity, fidelity, and reversibility of the proposed scheme are superior to existing RDH-ED methods, and fully separability is achieved without reducing the security of encryption

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

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

Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting

In recent years, reversible data hiding (RDH), a new research hotspot in the field of information security, has been paid more and more attention by researchers. Most of the existing RDH schemes do not fully take it into account that natural image's texture has influence on embedding distortion. The image distortion caused by embedding data in the image's smooth region is much smaller than that in the unsmooth region, essentially, it is because embedding additional data in the smooth region corresponds to fewer invalid shifting pixels (ISPs) in histogram shifting. Thus, we propose a RDH scheme based on the images texture to reduce invalid shifting of pixels in histogram shifting. Specifically, first, a cover image is divided into two sub-images by the checkerboard pattern, and then each sub-image's fluctuation values are calculated. Finally, additional data can be embedded into the region of sub-images with smaller fluctuation value preferentially. The experimental results demonstrate that the proposed method has higher capacity and better stego-image quality than some existing RDH schemes.Comment: 11 pages, 11 figures, 1 tabl

Generative Reversible Data Hiding by Image to Image Translation via GANs

The traditional reversible data hiding technique is based on cover image modification which inevitably leaves some traces of rewriting that can be more easily analyzed and attacked by the warder. Inspired by the cover synthesis steganography based generative adversarial networks, in this paper, a novel generative reversible data hiding scheme (GRDH) by image translation is proposed. First, an image generator is used to obtain a realistic image, which is used as an input to the image-to-image translation model with CycleGAN. After image translation, a stego image with different semantic information will be obtained. The secret message and the original input image can be recovered separately by a well-trained message extractor and the inverse transform of the image translation. Experimental results have verified the effectiveness of the scheme

Secret Image Sharing Using Grayscale Payload Decomposition and Irreversible Image Steganography

To provide an added security level most of the existing reversible as well as irreversible image steganography schemes emphasize on encrypting the secret image (payload) before embedding it to the cover image. The complexity of encryption for a large payload where the embedding algorithm itself is complex may adversely affect the steganographic system. Schemes that can induce same level of distortion, as any standard encryption technique with lower computational complexity, can improve the performance of stego systems. In this paper we propose a secure secret image sharing scheme, which bears minimal computational complexity. The proposed scheme, as a replacement for encryption, diversifies the payload into different matrices which are embedded into carrier image (cover image) using bit X-OR operation. A payload is a grayscale image which is divided into frequency matrix, error matrix, and sign matrix. The frequency matrix is scaled down using a mapping algorithm to produce Down Scaled Frequency (DSF) matrix. The DSF matrix, error matrix, and sign matrix are then embedded in different cover images using bit X-OR operation between the bit planes of the matrices and respective cover images. Analysis of the proposed scheme shows that it effectively camouflages the payload with minimum computation time

A reversible high embedding capacity data hiding technique for hiding secret data in images

As the multimedia and internet technologies are growing fast, the transmission of digital media plays an important role in communication. The various digital media like audio, video and images are being transferred through internet. There are a lot of threats for the digital data that are transferred through internet. Also, a number of security techniques have been employed to protect the data that is transferred through internet. This paper proposes a new technique for sending secret messages securely, using steganographic technique. Since the proposed system uses multiple level of security for data hiding, where the data is hidden in an image file and the stego file is again concealed in another image. Previously, the secret message is being encrypted with the encryption algorithm which ensures the achievement of high security enabled data transfer through internet.Comment: IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 7 No. 3, March 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis

When an attacker meets a cipher-image in 2018: A Year in Review

This paper aims to review the encountered technical contradictions when an attacker meets the cipher-images encrypted by the image encryption schemes (algorithms) proposed in 2018 from the viewpoint of an image cryptanalyst. The most representative works among them are selected and classified according to their essential structures. Almost all image cryptanalysis works published in 2018 are surveyed due to their small number. The challenging problems on design and analysis of image encryption schemes are summarized to receive the attentions of both designers and attackers (cryptanalysts) of image encryption schemes, which may promote solving scenario-oriented image security problems with new technologies.Comment: 12 page

An Evolutionary Computing Enriched RS Attack Resilient Medical Image Steganography Model for Telemedicine Applications

The recent advancement in computing technologies and resulting vision based applications have gives rise to a novel practice called telemedicine that requires patient diagnosis images or allied information to recommend or even perform diagnosis practices being located remotely. However, to ensure accurate and optimal telemedicine there is the requirement of seamless or flawless biomedical information about patient. On the contrary, medical data transmitted over insecure channel often remains prone to get manipulated or corrupted by attackers. The existing cryptosystems alone are not sufficient to deal with these issues and hence in this paper a highly robust reversible image steganography model has been developed for secret information hiding. Unlike traditional wavelet transform techniques, we incorporated Discrete Ripplet Transformation (DRT) technique for message embedding in the medical cover images. In addition, to assure seamless communication over insecure channel, a dual cryptosystem model containing proposed steganography scheme and RSA cryptosystem has been developed. One of the key novelties of the proposed research work is the use of adaptive genetic algorithm (AGA) for optimal pixel adjustment process (OPAP) that enriches data hiding capacity as well as imperceptibility features. The performance assessment reveals that the proposed steganography model outperforms other wavelet transformation based approaches in terms of high PSNR, embedding capacity, imperceptibility etc.Comment: 14 page / 3 figures / 6 tables, Multidimensional Systems and Signal Processing 201

Reversible Data Hiding in Encrypted Images using Local Difference of Neighboring Pixels

This paper presents a reversible data hiding in encrypted image (RDHEI), which divides image into non-overlapping blocks. In each block, central pixel of the block is considered as leader pixel and others as follower ones. The prediction errors between the intensity of follower pixels and leader ones are calculated and analyzed to determine a feature for block embedding capacity. This feature indicates the amount of data that can be embedded in a block. Using this pre-process for whole blocks, we vacate rooms before the encryption of the original image to achieve high embedding capacity. Also, using the features of all blocks, embedded data is extracted and the original image is perfectly reconstructed at the decoding phase. In effect, comparing to existent RDHEI algorithms, embedding capacity is significantly increased in the proposed algorithm. Experimental results confirm that the proposed algorithm outperforms state of the art ones