Real-Time Error-Free Reversible Data Hiding in Encrypted Images Using (7, 4) Hamming Code and Most Significant Bit Prediction

In this paper, a novel, real-time, error-free, reversible data hiding method for encrypted images has been proposed. Based on the (7, 4) Hamming code, we designed an efficient encoding scheme to embed secret data into the least significant bits (LSBs) of the encrypted image. For reversibility, we designed a most significant bit (MSB) prediction scheme that can recover a portion of the modified MSBs after the image is decrypted. These MSBs can be modified to accommodate the additional information that is used to recover the LSBs. After embedding the data, the original image can be recovered with no error and the secret data can be extracted from both the encrypted image and the decrypted image. The experimental results proved that compared with existing methods, the proposed method can achieve higher embedding rate, better quality of the marked image and less execution time of data embedding. Therefore, the proposed method is suitable for real-time applications in the cloud.

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High-Capacity Reversible Data Hiding in Encrypted Images by Information Preprocessing

Complexity ◽

10.1155/2020/6989452 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Xi-Yan Li ◽

Xia-Bing Zhou ◽

Qing-Lei Zhou ◽

Shi-Jing Han ◽

Zheng Liu

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

High Capacity ◽

Main Idea ◽

Original Image ◽

Chaos Encryption ◽

Secret Information ◽

Encrypted Image ◽

Encrypted Images ◽

Scanned Documents

With the development of cloud computing, high-capacity reversible data hiding in an encrypted image (RDHEI) has attracted increasing attention. The main idea of RDHEI is that an image owner encrypts a cover image, and then a data hider embeds secret information in the encrypted image. With the information hiding key, a receiver can extract the embedded data from the hidden image; with the encryption key, the receiver reconstructs the original image. In this paper, we can embed data in the form of random bits or scanned documents. The proposed method takes full advantage of the spatial correlation in the original images to vacate the room for embedding information before image encryption. By jointly using Sudoku and Arnold chaos encryption, the encrypted images retain the vacated room. Before the data hiding phase, the secret information is preprocessed by a halftone, quadtree, and S-BOX transformation. The experimental results prove that the proposed method not only realizes high-capacity reversible data hiding in encrypted images but also reconstructs the original image completely.

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Reversible Data Hiding in Encrypted Images Using Median Edge Detector and Two’s Complement

Symmetry ◽

10.3390/sym13060921 ◽

2021 ◽

Vol 13 (6) ◽

pp. 921

Author(s):

Rui Wang ◽

Guohua Wu ◽

Qiuhua Wang ◽

Lifeng Yuan ◽

Zhen Zhang ◽

...

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Personal Information ◽

Rapid Development ◽

Prediction Method ◽

Prediction Errors ◽

Edge Detector ◽

Secret Data ◽

Encrypted Images ◽

Cloud Servers

With the rapid development of cloud storage, an increasing number of users store their images in the cloud. These images contain many business secrets or personal information, such as engineering design drawings and commercial contracts. Thus, users encrypt images before they are uploaded. However, cloud servers have to hide secret data in encrypted images to enable the retrieval and verification of massive encrypted images. To ensure that both the secret data and the original images can be extracted and recovered losslessly, researchers have proposed a method that is known as reversible data hiding in encrypted images (RDHEI). In this paper, a new RDHEI method using median edge detector (MED) and two’s complement is proposed. The MED prediction method is used to generate the predicted values of the original pixels and calculate the prediction errors. The adaptive-length two’s complement is used to encode the most prediction errors. To reserve room, the two’s complement is labeled in the pixels. To record the unlabeled pixels, a label map is generated and embedded into the image. After the image has been encrypted, it can be embedded with the data. The experimental results indicate that the proposed method can reach an average embedding rate of 2.58 bpp, 3.04 bpp, and 2.94 bpp on the three datasets, i.e., UCID, BOSSbase, BOWS-2, which outperforms the previous work.

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Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image

Security and Communication Networks ◽

10.1155/2018/9103418 ◽

2018 ◽

Vol 2018 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Chunqiang Yu ◽

Xianquan Zhang ◽

Zhenjun Tang ◽

Yan Chen ◽

Jingyu Huang

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Data Extraction ◽

Visual Quality ◽

Input Image ◽

Embedding Capacity ◽

Secret Data ◽

Encrypted Image ◽

High Embedding Capacity ◽

Additive Homomorphism

Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.

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An Efficient Reversible Data Hiding Scheme for Encrypted Images

International Journal of Digital Crime and Forensics ◽

10.4018/ijdcf.2018040101 ◽

2018 ◽

Vol 10 (2) ◽

pp. 1-22 ◽

Cited By ~ 2

Author(s):

Kai Chen ◽

Dawen Xu

Keyword(s):

Data Hiding ◽

Efficient Method ◽

Reversible Data Hiding ◽

Additional Data ◽

Emerging Technology ◽

Experimental Results ◽

Cover Image ◽

Original Image ◽

Secret Data ◽

Encrypted Images

Reversible data hiding in the encrypted domain is an emerging technology, as it can preserve the confidentiality. In this article, an efficient method of reversible data hiding in encrypted images is proposed. The cover image is first partitioned into non-overlapping blocks. A specific modulo addition operation and block-scrambling operation are applied to obtain the encrypted image. The data-hider, who does not know the original image content, may reversibly embed secret data based on the homomorphic property of the cryptosystem. A scale factor is utilized for selecting embedding zone, which is scalable for different capacity requirements. At the receiving end, the additional data can be extracted if the receiver has the data-hiding key only. If the receiver has the encryption key only, he/she can recover the original image approximately. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original content without any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

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High Capacity Reversible Data Hiding Based on the Compression of Pixel Differences

Mathematics ◽

10.3390/math8091435 ◽

2020 ◽

Vol 8 (9) ◽

pp. 1435

Author(s):

Kai-Meng Chen

Keyword(s):

Spatial Correlation ◽

Data Hiding ◽

Reversible Data Hiding ◽

High Capacity ◽

Visual Quality ◽

Small Range ◽

Encryption Scheme ◽

Secret Data ◽

Encrypted Image ◽

Block Level

In this paper, we proposed a novel reversible data hiding method in encrypted image (RDHEI), which is based on the compression of pixel differences. In the proposed method, at the content owner’ side the image is divided into non-overlapping blocks, and a block-level image encryption scheme is used to generate the encrypted image, which partially retains spatial correlation in the blocks. Due to the spatial correlation, in each block the pixels are highly likely to be similar. Therefore, the pixel differences in all blocks are concentrated in a small range and can be compressed. By the compression of pixel differences, the data hider can vacate the room to accommodate secret data in the encrypted image without losing information. At the receiver’s side, the receiver can obtain secret data or retrieve the original image using different keys with no error. The experimental results demonstrate that, compared with existing methods, the proposed method can achieve a higher capacity and visual quality.

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Real-time reversible data hiding in encrypted images based on hybrid embedding mechanism

Journal of Real-Time Image Processing ◽

10.1007/s11554-018-0811-y ◽

2018 ◽

Vol 16 (3) ◽

pp. 697-708 ◽

Cited By ~ 5

Author(s):

Wei Zhang ◽

Ping Kong ◽

Heng Yao ◽

Yu-Chen Hu ◽

Fang Cao

Keyword(s):

Real Time ◽

Data Hiding ◽

Reversible Data Hiding ◽

Encrypted Images

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Separable Reversible Data Hiding in Encrypted Images Based on Two-Dimensional Histogram Modification

Security and Communication Networks ◽

10.1155/2018/1734961 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 6

Author(s):

Dawen Xu ◽

Kai Chen ◽

Rangding Wang ◽

Shubing Su

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Data Extraction ◽

Image Recovery ◽

Two Dimensional ◽

Secret Data ◽

Histogram Modification ◽

Encrypted Images ◽

Difference Histogram ◽

Image Difference

An efficient method of completely separable reversible data hiding in encrypted images is proposed. The cover image is first partitioned into nonoverlapping blocks and specific encryption is applied to obtain the encrypted image. Then, image difference in the encrypted domain can be calculated based on the homomorphic property of the cryptosystem. The data hider, who does not know the original image content, may reversibly embed secret data into image difference based on two-dimensional difference histogram modification. Data extraction is completely separable from image decryption; that is, data extraction can be done either in the encrypted domain or in the decrypted domain, so that it can be applied to different application scenarios. In addition, data extraction and image recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

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Reversible Data Hiding in Encrypted Image Based on (7, 4) Hamming Code and UnitSmooth Detection

Entropy ◽

10.3390/e23070790 ◽

2021 ◽

Vol 23 (7) ◽

pp. 790

Author(s):

Lin Li ◽

Chin-Chen Chang ◽

Chia-Chen Lin

Keyword(s):

Data Hiding ◽

Privacy Protection ◽

Reversible Data Hiding ◽

Signal To Noise Ratio ◽

Data Extraction ◽

Hamming Code ◽

Hiding Capacity ◽

Encrypted Images

With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) plays the dual role of privacy protection and secret information transmission. RDHEI has a good application prospect and practical value. The current RDHEI algorithms still have room for improvement in terms of hiding capacity, security and separability. Based on (7, 4) Hamming Code and our proposed prediction/ detection functions, this paper proposes a Hamming Code and UnitSmooth detection based RDHEI scheme, called HUD-RDHEI scheme for short. To prove our performance, two database sets—BOWS-2 and BOSSBase—have been used in the experiments, and peak signal to noise ratio (PSNR) and pure embedding rate (ER) are served as criteria to evaluate the performance on image quality and hiding capacity. Experimental results confirm that the average pure ER with our proposed scheme is up to 2.556 bpp and 2.530 bpp under BOSSBase and BOWS-2, respectively. At the same time, security and separability is guaranteed. Moreover, there are no incorrect extracted bits during data extraction phase and the visual quality of directly decrypted image is exactly the same as the cover image.

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Real-time reversible data hiding with shifting block histogram of pixel differences in encrypted image

Journal of Real-Time Image Processing ◽

10.1007/s11554-018-0838-0 ◽

2018 ◽

Vol 16 (3) ◽

pp. 709-724 ◽

Cited By ~ 5

Author(s):

Zhenjun Tang ◽

Shijie Xu ◽

Dengpan Ye ◽

Jinyan Wang ◽

Xianquan Zhang ◽

...

Keyword(s):

Real Time ◽

Data Hiding ◽

Reversible Data Hiding ◽

Encrypted Image

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Applying GMEI-GAN to Generate Meaningful Encrypted Images in Reversible Data Hiding Techniques

Symmetry ◽

10.3390/sym13122438 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2438

Author(s):

Chwei-Shyong Tsai ◽

Hsien-Chu Wu ◽

Yu-Wen Li ◽

Josh Jia-Ching Ying

Keyword(s):

Data Hiding ◽

Network Architecture ◽

Reversible Data Hiding ◽

Rapid Development ◽

Cover Image ◽

Generative Adversarial Networks ◽

Secret Data ◽

Residual Learning ◽

Encryption Decryption ◽

Encrypted Images

With the rapid development of information technology, the transmission of information has become convenient. In order to prevent the leakage of information, information security should be valued. Therefore, the data hiding technique has become a popular solution. The reversible data hiding technique (RDH) in particular uses symmetric encoding and decoding algorithms to embed the data into the cover carrier. Not only can the secret data be transmitted without being detected and retrieved completely, but the cover carrier also can be recovered without distortion. Moreover, the encryption technique can protect the carrier and the hidden data. However, the encrypted carrier is a form of ciphertext, which has a strong probability to attract the attention of potential attackers. Thus, this paper uses the generative adversarial networks (GAN) to generate meaningful encrypted images for RDH. A four-stage network architecture is designed for the experiment, including the hiding network, the encryption/decryption network, the extractor, and the recovery network. In the hiding network, the secret data are embedded into the cover image through residual learning. In the encryption/decryption network, the cover image is encrypted into a meaningful image, called the marked image, through GMEI-GAN, and then the marked image is restored to the decrypted image via the same architecture. In the extractor, 100% of the secret data are extracted through the residual learning framework, same as the hiding network. Lastly, in the recovery network, the cover image is reconstructed with the decrypted image and the retrieved secret data through the convolutional neural network. The experimental results show that using the PSNR/SSIM as the criteria, the stego image reaches 45.09 dB/0.9936 and the marked image achieves 38.57 dB/0.9654. The proposed method not only increases the embedding capacity but also maintains high image quality in the stego images and marked images.

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