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

Symmetry ◽  
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.

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

Symmetry ◽  
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.

An Efficient Reversible Data Hiding Scheme for Encrypted Images

2018 ◽  
Vol 10 (2) ◽  
pp. 1-22 ◽  
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.

scholarly journals A Location Map Reduced Reversible Data Hiding Method Using Prediction Error Modification

2012 ◽  
Vol 6-7 ◽  
pp. 428-433
Author(s):  
Yan Wei Li ◽  
Mei Chen Wu ◽  
Tung Shou Chen ◽  
Wien Hong
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Experimental Results ◽  
Cover Image ◽  
Prediction Errors ◽  
Secret Data ◽  
Location Map ◽  
Comparable Image Quality

We propose a reversible data hiding technique to improve Hong and Chen’s (2010) method. Hong and Chen divide the cover image into pixel group, and use reference pixels to predict other pixel values. Data are then embedded by modifying the prediction errors. However, when solving the overflow and underflow problems, they employ a location map to record the position of saturated pixels, and these pixels will not be used to carry data. In their method, if the image has a plenty of saturated pixels, the payload is decreased significantly because a lot of saturated pixels will not joint the embedment. We improve Hong and Chen’s method such that the saturated pixels can be used to carry data. The positions of these saturated pixels are then recorded in a location map, and the location map is embedded together with the secret data. The experimental results illustrate that the proposed method has better payload, will providing a comparable image quality.

scholarly journals Reversible data hiding scheme based on pixel-value differencing in dual images

2020 ◽  
Vol 16 (7) ◽  
pp. 155014772091100
Author(s):  
Pyung-Han Kim ◽  
Kwan-Woo Ryu ◽  
Ki-Hyun Jung
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Cover Image ◽  
Maximum Difference ◽  
Secret Data ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
Dual Images

In this article, a new reversible data hiding scheme using pixel-value differencing in dual images is proposed. The proposed pixel-value differencing method can embed more secret data as the difference value of adjacent pixels is increased. In the proposed scheme, the cover image is divided into non-overlapping blocks and the maximum difference value is calculated to hide secret bits. On the sender side, the length of embeddable secret data is calculated by using the maximum difference value and the log function, and the decimal secret data are embedded into the two stego-images after applying the ceil function and floor function. On the receiver side, the secret data extraction and the cover image restoration can be performed by using the correlation between two stego-images. After recovering the cover image from two stego-images, the secret data can be extracted using the maximum difference value and the log function. The experimental results show that the proposed scheme has a higher embedding capacity and the proposed scheme differs in embedding the secret data depending on the characteristics of the cover image with less distortion. Also, the proposed scheme maintains the degree of image distortion that cannot be perceived by the human visual system.

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

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
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.

Block-Based Reversible Data Hiding Using Histogram Shifting and Modulus Operator for Digital Images

2017 ◽  
Vol 26 (06) ◽  
pp. 1750103 ◽  
Author(s):  
Pankaj Garg ◽  
Singara Singh Kasana ◽  
Geeta Kasana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Signal To Noise ◽  
Secret Data ◽  
Peak Points ◽  
Block Based

A Reversible Data Hiding technique by using histogram shifting and modulus operator is proposed in which secret data is embedded into blocks of the cover image. These blocks are modified by using modulus operator to increase the number of peak points in the histogram of the cover image which further increases its embedding capacity. Secret data is embedded in the original cover blocks of the cover image by using peak points of the predicted blocks, which are generated by using modulus operator. Peak Signal to Noise Ratio and PSNR-Human Visual System are used to show the human visual acceptance of the proposed technique. Experimental results show that the embedding capacity is high as compared to the capacity of existing RDH techniques, while distortion in marked images is also less as compared to distortion produced by these existing techniques.

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

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 51 ◽  
Author(s):  
Kaimeng Chen ◽  
Chin-Chen Chang
Keyword(s):  
Real Time ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Hamming Code ◽  
Time Error ◽  
Secret Data ◽  
Encrypted Image ◽  
Additional Information ◽  
Prediction Scheme ◽  
Encrypted Images

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.

scholarly journals High-Capacity Reversible Data Hiding in Encrypted Images Based on Adaptive Predictor and Compression of Prediction Errors

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2166
Author(s):  
Bin Huang ◽  
Chun Wan ◽  
Kaimeng Chen
Keyword(s):  
Image Encryption ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Huffman Coding ◽  
Prediction Errors ◽  
Original Image ◽  
Embedding Capacity ◽  
Secret Data ◽  
Encrypted Images

Reversible data hiding in encrypted images (RDHEI) is a technology which embeds secret data into encrypted images in a reversible way. In this paper, we proposed a novel high-capacity RDHEI method which is based on the compression of prediction errors. Before image encryption, an adaptive linear regression predictor is trained from the original image. Then, the predictor is used to obtain the prediction errors of the pixels in the original image, and the prediction errors are compressed by Huffman coding. The compressed prediction errors are used to vacate additional room with no loss. After image encryption, the vacated room is reserved for data embedding. The receiver can extract the secret data and recover the image with no errors. Compared with existing approaches, the proposed method efficiently improves the embedding capacity.

Use of firefly optimization algorithm for fractional fourier transform based reversible data hiding

2021 ◽  
Vol 40 (1) ◽  
pp. 415-425
Author(s):  
A. Amsaveni ◽  
M. Bharathi
Keyword(s):  
Fourier Transform ◽  
Data Hiding ◽  
Bit Error Rate ◽  
Error Rate ◽  
Reversible Data Hiding ◽  
Firefly Algorithm ◽  
Fractional Fourier Transform ◽  
Cover Image ◽  
Secret Data ◽  
Time Frequency

This paper presents a Fractional Fourier transform based reversible data hiding technique to secure the data transmitted over communication network. The proposed algorithm modifies the cover image to improve the robustness of data hiding technique. The cover image is transformed using Fractional Fourier Transform (FrFT) into a time-frequency domain and the optimal pixel locations for hiding the secret data are found using firefly algorithm. Firefly algorithm uses multi-objective function, which is a combination of Structural Similarity Index Measure (SSIM) and Bit Error rate (BER). The histogram shifting technique embeds secret data in the optimal pixel locations. The quality of test images is analyzed under varying payload as well as under varying fractional order. Experimental results conclude that this scheme produces good quality stego image. It has also been found from the simulation results that the proposed algorithm is more robust and reversible against various attacks as it provides lower bit error rate and higher normalization coefficient.

scholarly journals Generalized Reversible Data Hiding with Content-Adaptive Operation and Fast Histogram Shifting Optimization

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 917
Author(s):  
Limengnan Zhou ◽  
Hongyu Han ◽  
Hanzhou Wu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Hot Spot ◽  
Data Embedding ◽  
Histogram Shifting ◽  
Secret Data ◽  
Content Selection ◽  
Wide Range ◽  
Map Generation ◽  
Content Adaptive

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

Sign in / Sign up

Export Citation Format

Share Document