Reversible data hiding in encrypted images based on pixel prediction and multi-MSB planes rearrangement

Yin, Zhaoxia; She, Xiaomeng; Tang, Jin; Luo, Bin

doi:10.1016/j.sigpro.2021.108146

Cited by 51 publications

(25 citation statements)

References 29 publications

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“…Unlike VRAE, the RRBE research requires a pre-processing operation to be completed prior to image encryption to release the embedding space, or more precisely, to create space in the plaintext domain [20][21][22][23][24][25][26][27][28][29][30][31]. Ma et al [20] proposed the first RRBE solution for dealing with capacity and visual quality issues in VRAE.…”

Section: Introductionmentioning

confidence: 99%

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Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Ren

Yue

2023

Preprint

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With the rapid development of network technology and the massive accumulation of user data, huge amounts of data are being rapidly generated and shared on the network, while the problems of unauthorized data access and misuse continue to emerge. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data into encrypted content and accurately extracts the embedded data without affecting the original content. However, the amount of embedded protected information has always been one of the major constraints on the performance and application of RDHEI. Currently, the main approaches to improve the net embedding capacity of RDHEI are to increase the total embedding capacity or to reduce the length of the auxiliary information to be embedded. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the total embedding capacity, we use the MED + GAP predictor to generate the label map data of non-reference pixels before image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels to reduce the embedding length of the auxiliary information used for extraction and recovery. Experimental results show that with MED + GAP predictor and adaptive Huffman coding, the proposed method achieves a higher embedding capacity than other recent methods while ensuring security and reversibility.

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Section: Introductionmentioning

confidence: 99%

“…To better exploit the correlation between adjacent pixels, Cao et al [22] considered a sparse representation at the image block level when concealing secret data. Yin et al [23] embedded more secret information into the reserved space by pixel prediction and multi-MSB rearrangement.…”

Section: Introductionmentioning

confidence: 99%

Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Ren

Yue

2023

Preprint

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“…To meet different security requirements, many improved RDH-EI schemes have been proposed [13,[17][18][19]. Yi and Zhou [13] designed a RDH algorithm based on parametric binary tree labeling (PBTL), making full use of the spatial redundancy of the image, and solved the problem of low embedding rate (ER).…”

Section: Introductionmentioning

confidence: 99%

“…Wu et al [17] proposed an improved parametric binary tree labeling (IPBTL) RDH-EI method and achieved a higher ER than [13], but has low utilization of spatial redundancy. Meanwhile, Yin et al proposed an RDH encryption image algorithm based on pixel prediction and multi-MSB plane rearrangement [18], which solved the problem of large space for auxiliary information through arithmetic coding and data compression, and introduced the medium edge detector (MED) that improves ER. Subsequently, Yang et al [19] introduced block scrambling in the encryption algorithm and adaptive coding in the embedding process to improve the compression rate and embedding ability.…”

Section: Introductionmentioning

confidence: 99%

Reversible Data Hiding in Encrypted Images Based on Adaptive Gradient Prediction

Qin

Xiang

et al. 2022

Security and Communication Networks

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The existing reversible data hiding (RDH) technology solves the problem that the ciphertext data and carrier are easily damaged in the traditional scheme, which has become a research hotspot in information hiding. However, because of the small coverage area of the predictor and poor prediction ability of the existing reversible data hiding in encrypted images (RDH-EI) technology based on pixel predictor, the embedding performance of the algorithm is limited. Therefore, this paper proposes an adaptive gradient prediction (AGP) scheme. The AGP employs a comprehensive and efficient local complexity measurement strategy to make predictions based on pixel changes around the predicted pixel, including horizontal, vertical, and diagonal directions. The experimental results show that the AGP-RDHEI scheme has apparent advantages in embedding rate.

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“…By iterating the chaotic system and outputting random sequence, the source point of wavelet transmission was determined. Rood operation was introduced to scramble plaintext, and the encryption model was built by relying on plaintext content and key [ 7 ]. Although the algorithm in literature has good performance, the information embedding side can only embed the information in the space reserved before encryption.…”

Section: Introductionmentioning

confidence: 99%

Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

Ding

Yun-bo

Zhang

et al. 2021

Contrast Media & Molecular Imaging

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Aiming at the shortcomings of the existing lossless digital watermarking algorithm based on frequency domain in reversibility and embedding capacity, this study proposes a lossless digital image watermarking algorithm based on fractional wavelet transform, which is used for large-capacity reversible information hiding of images. First, the image is transformed by LeGall5/3 fractional wavelet, and then, the watermark is embedded in the high-frequency subband by the histogram shift method. In order to obtain maximum embedding capacity and reduce image distortion, the methods of selecting embedding parameters and stopping parameters are proposed, respectively. At the same time, in order to prevent overflow and reduce additional information, a new method of generating position map is proposed. The experimental results show that Lena is the result of multilayer embedding based on the algorithm in this study. In order to better observe the distortion phenomenon and enlarge the image, the Lena test image is the watermark image obtained after two and three layers of embedding, and its embedding capacity can be 2.7 bpp. It is proved that wavelet transform is suitable for encrypted images to implement covert communication.

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Reversible data hiding in encrypted images based on pixel prediction and multi-MSB planes rearrangement

Cited by 51 publications

References 29 publications

Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Reversible Data Hiding in Encrypted Images Based on Adaptive Gradient Prediction

Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

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