scholarly journals Separable Reversible Data Hiding in Encrypted Images Based on Difference Histogram Modification

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Dawen Xu ◽  
Shubing Su
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Linear Prediction ◽  
Data Extraction ◽  
Histogram Modification ◽  
Modulo Operation ◽  
Before And After ◽  
Hidden Data ◽  
Encrypted Images ◽  
Difference Histogram

In this paper, an efficient reversible data hiding method for encrypted image based on neighborhood prediction is proposed, which includes image encryption, reversible data hiding in encrypted domain, and hidden data extraction. The cover image is first partitioned into non-overlapping blocks, and then the pixel value in each block is encrypted by modulo operation. Therefore, the linear prediction difference in the block that satisfies the specific condition is consistent before and after encryption, ensuring that data extraction is completely separable from image decryption. In addition, by using the linear weighting of three adjacent pixels in the block to predict the current pixel, the prediction accuracy can be improved. The data-hider, who does not know the original image content, may embed additional data based on prediction difference histogram modification. Data extraction and image recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

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.

Reversible Audio Data Hiding in Spectral and Time Domains

2013 ◽  
pp. 19-41 ◽  
Author(s):  
Akira Nishimura
Keyword(s):  
Data Hiding ◽  
Time Domain ◽  
Reversible Data Hiding ◽  
Linear Prediction ◽  
Data Consistency ◽  
Time Domains ◽  
Audio Data ◽  
Hidden Data ◽  
The Time Domain ◽  
Location Map

Reversible data hiding is a technique whereby hidden data are embedded in host data in such a way that the host data consistency is perfectly preserved and the host data are restored when extracting the hidden data. This chapter introduces basic algorithms for reversible data hiding, histogram shifting, histogram expansion, and compression. This chapter also proposes and evaluates two reversible data hiding methods, i.e., hiding data in the frequency-domain using integer Discrete Cosine Transform (DCT) and modified DCT and hiding in the time domain using linear prediction and error expansion. As no location map is required to prevent amplitude overflow, the proposed method in the time domain achieves a storage capacity of nearly 1 bit per sample of payload data. The proposed methods are evaluated by the payload amount, objective quality degradation of stego signal, and payload concealment.

scholarly journals A Joint Encryption and Reversible Data Hiding Scheme Based on Integer-DWT and Arnold Map Permutation

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Shun Zhang ◽  
Tiegang Gao ◽  
Guorui Sheng
Keyword(s):  
Frequency Domain ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Original Image ◽  
Histogram Modification ◽  
Encrypted Image ◽  
Hidden Data ◽  
Arnold Map

A joint encryption and reversible data hiding (joint encryption-RDH) scheme is proposed in this paper. The cover image is transformed to the frequency domain with integer discrete wavelet transform (integer DWT) for the encryption and data hiding. Additional data is hidden into the permuted middle (LH, HL) and high (HH) frequency subbands of integer DWT coefficients with a histogram modification based method. A combination of permutations both in the frequency domain and in the spatial domain is imposed for the encryption. In the receiving end, the encrypted image with hidden data can be decrypted to the image with hidden data, which is similar to the original image without hidden data, by only using the encryption key; if someone has both the data hiding key and the encryption key, he can both extract the hidden data and reversibly recover the original image. Experimental results demonstrate that, compared with existing joint encryption-RDH schemes, the proposed scheme has gained larger embedding capacity, and the distribution of the encrypted image with data hidden has a random like behavior. It can also achieve the lossless restoration of the cover image.

scholarly journals A Reversible Data Hiding Method in Encrypted Images for Controlling Trade-Off between Hiding Capacity and Compression Efficiency

2021 ◽  
Vol 7 (12) ◽  
pp. 268
Author(s):  
Ryota Motomura ◽  
Shoko Imaizumi ◽  
Hitoshi Kiya
Keyword(s):  
Data Hiding ◽  
Image Coding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Lossless Compression ◽  
The Other ◽  
Compression Efficiency ◽  
Hiding Capacity ◽  
Encrypted Images ◽  
New Framework

In this paper, we propose a new framework for reversible data hiding in encrypted images, where both the hiding capacity and lossless compression efficiency are flexibly controlled. There exist two main purposes; one is to provide highly efficient lossless compression under a required hiding capacity, while the other is to enable us to extract an embedded payload from a decrypted image. The proposed method can decrypt marked encrypted images without data extraction and derive marked images. An original image is arbitrarily divided into two regions. Two different methods for reversible data hiding in encrypted images (RDH-EI) are used in our method, and each one is used for either region. Consequently, one region can be decrypted without data extraction and also losslessly compressed using image coding standards even after the processing. The other region possesses a significantly high hiding rate, around 1 bpp. Experimental results show the effectiveness of the proposed method in terms of hiding capacity and lossless compression efficiency.

scholarly journals High-Capacity Reversible Data Hiding in Encrypted Images Based on Hierarchical Quad-Tree Coding and Multi-MSB Prediction

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 664
Author(s):  
Ya Liu ◽  
Guangdong Feng ◽  
Chuan Qin ◽  
Haining Lu ◽  
Chin-Chen Chang
Keyword(s):  
Data Hiding ◽  
Prediction Error ◽  
Reversible Data Hiding ◽  
Cloud Storage ◽  
Additional Data ◽  
State Of The Art ◽  
Data Extraction ◽  
High Capacity ◽  
Quad Tree ◽  
Encrypted Images

Nowadays, more and more researchers are interested in reversible data hiding in encrypted images (RDHEI), which can be applied in privacy protection and cloud storage. In this paper, a new RDHEI method on the basis of hierarchical quad-tree coding and multi-MSB (most significant bit) prediction is proposed. The content owner performs pixel prediction to obtain a prediction error image and explores the maximum embedding capacity of the prediction error image by hierarchical quad-tree coding before image encryption. According to the marked bits of vacated room capacity, the data hider can embed additional data into the room-vacated image without knowing the content of original image. Through the data hiding key and the encryption key, the legal receiver is able to conduct data extraction and image recovery separately. Experimental results show that the average embedding rates of the proposed method can separately reach 3.504 bpp (bits per pixel), 3.394 bpp, and 2.746 bpp on three well-known databases, BOSSBase, BOWS-2, and UCID, which are higher than some state-of-the-art methods.

scholarly journals Separable Data-Hiding Scheme for Encrypted Image to Protect Privacy of User in Cloud

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 82 ◽  
Author(s):  
Li Liu ◽  
Lifang Wang ◽  
Yun-Qing Shi ◽  
Chin-Chen Chang
Keyword(s):  
Cloud Computing ◽  
Compressive Sensing ◽  
Data Hiding ◽  
Data Extraction ◽  
Data Loss ◽  
Hiding Capacity ◽  
Encrypted Image ◽  
Private Data ◽  
Hidden Data ◽  
Encrypted Images

As cloud computing becomes popular, the security of users’ data is faced with a great threat, i.e., how to protect users’ privacy has become a pressing research topic. The combination of data hiding and encryption can provide dual protection for private data during cloud computing. In this paper, we propose a new separable data-hiding scheme for encrypted images based on block compressive sensing. First, the original uncompressed image is compressed and encrypted by block compressive sensing (BCS) using a measurement matrix, which is known as an encryption key. Then, some additional data can be hidden into the four least significant bits of measurement using the data-hiding key during the process of encoding. With an encrypted image that contains hidden data, the receiver can extract the hidden data or decrypt/reconstruct the protected private image, according to the key he/she possesses. This scheme has important features of flexible compression and anti-data-loss. The image reconstruction and data extraction are separate processes. Experimental results have proven the expected merits of the proposed scheme. Compared with the previous work, our proposed scheme reduces the complexity of the scheme and also achieves better performance in compression, anti-data-loss, and hiding capacity.

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