Reversible Data Hiding in Encrypted Images Using Interpolation and Histogram Shifting

2015 ◽  
pp. 230-242 ◽  
Author(s):  
Dawen Xu ◽  
Rangding Wang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Histogram Shifting ◽  
Encrypted Images

scholarly journals Reversible Data Hiding in Encrypting Images - An System

2019 ◽  
Vol 8 (6) ◽  
pp. 3051-3053
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Original Data ◽  
Histogram Shifting ◽  
Compression Technique ◽  
The People ◽  
Expansion Technique ◽  
Image Technique ◽  
Image Pixels ◽  
Encrypted Images

In today’s technology data hiding has become an essential need due to the availability of the internet all over the world. Nowadays, it has become necessary task for the people to communicate through networks and share contents with each other. In the meanwhile, transferring the data in a secured manner has become a challenge and also a paradigm. Still there exists many ways for hiding the data in an encrypted images. Hiding information at the back end of the image should not affect the original data or image pixels. It is one type of steganographical method where the data can be hidden inside the images and original data can be losslessly retrieved after extracting the embedded text.The proposed work discusses encryption using reversible data hiding and produces an outlineof various reversible data hiding techniques which includes quantization technique, histogram shifting, expansion technique, compression technique anddual image technique

scholarly journals A Reversible Data Hiding Scheme in Encrypted Images for Medical Applications

2021 ◽  
pp. 166-172
Author(s):  
Dr. Rohith S ◽  
Harish V
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Image Recovery ◽  
Perceptual Quality ◽  
Medical Applications ◽  
Histogram Shifting ◽  
Novel Method ◽  
Encrypted Images ◽  
Excellent Property

Storage and exchange of data of the patient images are common in medical applications. To protect the information of the patient and to avoid miss handling of the patient information data hiding scheme is very much essential. Reversible Data Hiding (RDH) scheme is one such scheme paid more attention to hide the data in encrypted images, since it maintains the excellent property that the original cover can be lossless recovered after embedded data is extracted while protecting the image content’s confidentiality. In this paper initially space is reserved from the encrypted images, which may be used to embed the information later stage. Histogram shifting based Reversible Data Hiding scheme used to reserve the room before encryption process. 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 and achieves better perceptual quality.

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.

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

Complexity ◽  
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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