Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption
01 Mar 2013-IEEE Transactions on Information Forensics and Security (IEEE)-Vol. 8, Iss: 3, pp 553-562
TL;DR: This paper proposes a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image.
Abstract: Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content's confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error. Experiments show that this novel method can embed more than 10 times as large payloads for the same image quality as the previous methods, such as for PSNR=40 dB.
Citations
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TL;DR: In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RD h into image compressed domain (e.g., JPEG); 3) RDh suitable for image semi-fragile authentication; 4)RDH with image contrast enhancement; 5) RD H into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDD into video and into audio.
Abstract: In the past two decades, reversible data hiding (RDH), also referred to as lossless or invertible data hiding, has gradually become a very active research area in the field of data hiding. This has been verified by more and more papers on increasingly wide-spread subjects in the field of RDH research that have been published these days. In this paper, the various RDH algorithms and researches have been classified into the following six categories: 1) RDH into image spatial domain; 2) RDH into image compressed domain (e.g., JPEG); 3) RDH suitable for image semi-fragile authentication; 4) RDH with image contrast enhancement; 5) RDH into encrypted images, which is expected to have wide application in the cloud computation; and 6) RDH into video and into audio. For each of these six categories, the history of technical developments, the current state of the arts, and the possible future researches are presented and discussed. It is expected that the RDH technology and its applications in the real word will continue to move ahead.
432 citations
Cites methods from "Reversible Data Hiding in Encrypted..."
...In [158], the embedding room is created in digital images by embedding LSBs of certain pixels into other pixels using a traditional RDH method....
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..., vacating embedding room before encryption [158]–[161]....
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TL;DR: This paper proposes to consider the patch-level sparse representation when hiding the secret data, and significantly outperforms the state-of-the-art methods in terms of the embedding rate and the image quality.
Abstract: Reversible data hiding in encrypted images has attracted considerable attention from the communities of privacy security and protection. The success of the previous methods in this area has shown that a superior performance can be achieved by exploiting the redundancy within the image. Specifically, because the pixels in the local structures (like patches or regions) have a strong similarity, they can be heavily compressed, thus resulting in a large hiding room. In this paper, to better explore the correlation between neighbor pixels, we propose to consider the patch-level sparse representation when hiding the secret data. The widely used sparse coding technique has demonstrated that a patch can be linearly represented by some atoms in an over-complete dictionary. As the sparse coding is an approximation solution, the leading residual errors are encoded and self-embedded within the cover image. Furthermore, the learned dictionary is also embedded into the encrypted image. Thanks to the powerful representation of sparse coding, a large vacated room can be achieved, and thus the data hider can embed more secret messages in the encrypted image. Extensive experiments demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of the embedding rate and the image quality.
323 citations
Cites methods or result from "Reversible Data Hiding in Encrypted..."
...To overcome this drawback, the methods of reserving room before encryption (RRBE) are proposed [28], [29]....
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...For RRBE, two major proposed methods are [28] and [29]....
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...PSNR comparison for the directly decrypted images with the methods [23]–[29]....
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...In [29], the reserving room is obtained by embedding LSBs of some pixels into other pixels....
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...Specifically, in the most state-of-the-art RRBE method [29], the spare space emptied out is limited to at most three LSB-planes....
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TL;DR: This paper proposes a new reversible method based on MSB (most significant bit) prediction with a very high capacity, which is better than current state of the art methods, both in terms of reconstructed image quality and embedding capacity.
Abstract: Reversible data hiding in encrypted images (RDHEI) is an effective technique to embed data in the encrypted domain. An original image is encrypted with a secret key and during or after its transmission, it is possible to embed additional information in the encrypted image, without knowing the encryp-tion key or the original content of the image. During the decoding process, the secret message can be extracted and the original image can be reconstructed. In the last few years, RDHEI has started to draw research interest. Indeed, with the development of cloud computing, data privacy has become a real issue. However, none of the existing methods allow us to hide a large amount of information in a reversible manner. In this paper, we propose a new reversible method based on MSB (most significant bit) prediction with a very high capacity. We present two approaches, these are: high capacity reversible data hiding approach with correction of prediction errors and high capacity reversible data hiding approach with embedded prediction errors. With this method, regardless of the approach used, our results are better than those obtained with current state of the art methods, both in terms of reconstructed image quality and embedding capacity.
258 citations
Cites background or methods from "Reversible Data Hiding in Encrypted..."
...were the first to describe a RRBE technique [12]....
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...The space to embed the message may be vacated after or before the encryption phase and, during the decoding phase, image reconstruction and data extraction can be processed at the same time [17], [27] or separately [12], [27], [28]....
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TL;DR: A novel scheme of reversible data hiding in encrypted images using distributed source coding using Slepian-Wolf encoded using low-density parity check codes that outperforms the previously published ones.
Abstract: This paper proposes a novel scheme of reversible data hiding in encrypted images using distributed source coding. After the original image is encrypted by the content owner using a stream cipher, the data-hider compresses a series of selected bits taken from the encrypted image to make room for the secret data. The selected bit series is Slepian–Wolf encoded using low-density parity check codes. On the receiver side, the secret bits can be extracted if the image receiver has the embedding key only. In case the receiver has the encryption key only, he/she can recover the original image approximately with high quality using an image estimation algorithm. If the receiver has both the embedding and encryption keys, he/she can extract the secret data and perfectly recover the original image using the distributed source decoding. The proposed method outperforms the previously published ones.
241 citations
Cites background or methods from "Reversible Data Hiding in Encrypted..."
...Comparison of approximately recovered image quality in (a) [11] and (b) [13]....
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...Although VRBE can achieve a higher payload, it requires that the sender must perform an extra RDH before image encryption....
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...For example, the method in [11] creates embedding room in the plaintext image by embedding LSBs of certain pixels into other pixels using a traditional RDH method....
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...When comparing with VRBE methods, embedding payload of the proposed method is not as large as that of [11], which...
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...As to the embedding payload, VRBE substantially outperforms the previous VRAE method because VRBE has the advantage of handling the plaintext image by the sender....
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TL;DR: This paper proposes lossless, reversible, and combined data hiding schemes for ciphertext images encrypted by public-key cryptosystems with probabilistic and homomorphic properties.
Abstract: This paper proposes lossless, reversible, and combined data hiding schemes for ciphertext images encrypted by public-key cryptosystems with probabilistic and homomorphic properties. In the lossless scheme, the ciphertext pixels are replaced with new values to embed the additional data into several least significant bit planes of ciphertext pixels by multilayer wet paper coding. Then, the embedded data can be directly extracted from the encrypted domain, and the data-embedding operation does not affect the decryption of original plaintext image. In the reversible scheme, a preprocessing is employed to shrink the image histogram before image encryption, so that the modification on encrypted images for data embedding will not cause any pixel oversaturation in plaintext domain. Although a slight distortion is introduced, the embedded data can be extracted and the original image can be recovered from the directly decrypted image. Due to the compatibility between the lossless and reversible schemes, the data-embedding operations in the two manners can be simultaneously performed in an encrypted image. With the combined technique, a receiver may extract a part of embedded data before decryption, and extract another part of embedded data and recover the original plaintext image after decryption.
230 citations
Cites background from "Reversible Data Hiding in Encrypted..."
...If the creation of sparse data space or the compression is implemented before encryption, a better performance can be achieved [18], [19]....
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References
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Book•
01 Jan 1996TL;DR: A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols.
Abstract: From the Publisher:
A valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography, this book provides easy and rapid access of information and includes more than 200 algorithms and protocols; more than 200 tables and figures; more than 1,000 numbered definitions, facts, examples, notes, and remarks; and over 1,250 significant references, including brief comments on each paper.
13,597 citations
"Reversible Data Hiding in Encrypted..." refers background in this paper
...K. Ma, W. Zhang, and N. Yu are with the School of Information Science and Technology, University of Science and Technology of China, Hefei, 230026, China (e-mail: k29ma@uwaterloo.ca; weimingzhang@yahoo.cn; ynh@ustc.edu.cn)....
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...This work was supported in part by the Natural Science Foundation of China under Grant 61170234 and Grant 60803155, and in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA06030601....
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...X. Zhao and F. Li are with the State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China (e-mail: zhaoxianfeng@iie.ac.cn; lifenghua@iie.ac.cn)....
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TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
Abstract: Reversible data embedding has drawn lots of interest recently Being reversible, the original digital content can be completely restored We present a novel reversible data-embedding method for digital images We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low
2,739 citations
"Reversible Data Hiding in Encrypted..." refers methods in this paper
...This work was supported in part by the Natural Science Foundation of China under Grant 61170234 and Grant 60803155, and in part by the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant XDA06030601....
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TL;DR: It is proved analytically and shown experimentally that the peak signal-to-noise ratio of the marked image generated by this method versus the original image is guaranteed to be above 48 dB, which is much higher than that of all reversible data hiding techniques reported in the literature.
Abstract: A novel reversible data hiding algorithm, which can recover the original image without any distortion from the marked image after the hidden data have been extracted, is presented in this paper. This algorithm utilizes the zero or the minimum points of the histogram of an image and slightly modifies the pixel grayscale values to embed data into the image. It can embed more data than many of the existing reversible data hiding algorithms. It is proved analytically and shown experimentally that the peak signal-to-noise ratio (PSNR) of the marked image generated by this method versus the original image is guaranteed to be above 48 dB. This lower bound of PSNR is much higher than that of all reversible data hiding techniques reported in the literature. The computational complexity of our proposed technique is low and the execution time is short. The algorithm has been successfully applied to a wide range of images, including commonly used images, medical images, texture images, aerial images and all of the 1096 images in CorelDraw database. Experimental results and performance comparison with other reversible data hiding schemes are presented to demonstrate the validity of the proposed algorithm.
2,240 citations
TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.
Abstract: Reversible watermarking enables the embedding of useful information in a host signal without any loss of host information. Tian's difference-expansion technique is a high-capacity, reversible method for data embedding. However, the method suffers from undesirable distortion at low embedding capacities and lack of capacity control due to the need for embedding a location map. We propose a histogram shifting technique as an alternative to embedding the location map. The proposed technique improves the distortion performance at low embedding capacities and mitigates the capacity control problem. We also propose a reversible data-embedding technique called prediction-error expansion. This new technique better exploits the correlation inherent in the neighborhood of a pixel than the difference-expansion scheme. Prediction-error expansion and histogram shifting combine to form an effective method for data embedding. The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion. There is also a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities
1,229 citations
"Reversible Data Hiding in Encrypted..." refers background in this paper
...K. Ma, W. Zhang, and N. Yu are with the School of Information Science and Technology, University of Science and Technology of China, Hefei, 230026, China (e-mail: k29ma@uwaterloo.ca; weimingzhang@yahoo.cn; ynh@ustc.edu.cn)....
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10 Dec 2002
TL;DR: A prediction-based conditional entropy coder which utilizes static portions of the host as side-information improves the compression efficiency, and thus the lossless data embedding capacity.
Abstract: We present a novel reversible (lossless) data hiding (embedding) technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known LSB (least significant bit) modification is proposed as the data embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion, and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes static portions of the host as side-information improves the compression efficiency, and thus the lossless data embedding capacity.
1,126 citations
"Reversible Data Hiding in Encrypted..." refers background in this paper
...K. Ma, W. Zhang, and N. Yu are with the School of Information Science and Technology, University of Science and Technology of China, Hefei, 230026, China (e-mail: k29ma@uwaterloo.ca; weimingzhang@yahoo.cn; ynh@ustc.edu.cn)....
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