Efficient Data Embedding for Interpolation based Reversible Data Hiding Scheme

2017 ◽  
Author(s):  
Md. Abdul Wahed ◽  
Hussain Nyeem
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Embedding ◽  
Efficient Data

A Reversible Data Hiding for JPEG Images

2012 ◽  
Vol 433-440 ◽  
pp. 4615-4620 ◽  
Author(s):  
Gui Long Liao ◽  
Xin Peng Zhang
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Rate Distortion ◽  
Previous Method ◽  
Data Embedding ◽  
Original Image ◽  
Secret Data ◽  
Jpeg Images ◽  
Efficient Data ◽  
Dct Coefficients

A novel reversible data hiding technique for JPEG images is proposed in this paper. Consecutive zeros in the tail of DCT coefficient sequence in each block are exploited to embed a number of secret bits by modifying only one coefficient. Thanks to the efficient data embedding in the DCT coefficients, the proposed scheme can provide a good rate-distortion performance. Also, when having an image containing secret data, one can perfectly recover the original image after extracting the embedded data. Experimental results show that the proposed scheme outperforms the previous method.

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 Reversible Data Hiding in Encrypted Images With Dual Data Embedding

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 23209-23220
Author(s):  
Yingqiang Qiu ◽  
Qichao Ying ◽  
Xiaodan Lin ◽  
Yaowen Zhang ◽  
Zhenxing Qian
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Embedding ◽  
Encrypted Images

FPGA Realization of a Reversible Data Hiding Scheme for 5G MIMO-OFDM System by Chaotic Key Generation-Based Paillier Cryptography Along with LDPC and Its Side Channel Estimation Using Machine Learning Technique

2021 ◽  
Author(s):  
Francis H. Shajin ◽  
P. Rajesh
Keyword(s):  
Machine Learning ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Performance Metrics ◽  
Security Analysis ◽  
Key Generation ◽  
Data Embedding ◽  
Machine Learning Technique ◽  
Packet Delivery ◽  
Learning Technique

Multiple-Input and Multiple-Output (MIMO) technology is a significant and timely subject, which is highly motivated by the needs of 5G wireless communications. Data transmission performs MIMO, which is highly sensitive. There are several security issues while transmitting the data such as loss of data and code injection. Two efficient methods are Encryption and Data Hiding protection of data in wireless communication. This dissertation suggests FPGA Implementation of RDHS by Chaotic Key Generation-Based Paillier Cryptography with LDPC using machine learning technique. RDHS stands for Reversible Data Hiding Scheme. In a reversible method, the initial stage of preprocessing is to shrink the histogram of image before the process of encryption. Hence, the plaintext domain changing the encrypted images to data embedding cannot result from any pixel repletion. A little distortion data embedding may be taken as the original image may recover the directly decrypted image. Here, the performance metrics of throughput, area consumed, latency, delay, packet delivery, network life and overhead are calculated. The proposed Paillier homomorphic cryptosystem proposes higher network throughput as 99%, higher network life 98%, lower delay rate as 60%, packet delivery as 74%, overhead as 66%, latency as 55% and area consumed as 61% with the existing method such as McEliece, Elgamal and Elliptic curve cryptosystem in the security analysis of the proposed method providing decryption time 94% and encryption time 98% better than the existing method.

scholarly journals Reversible Data Hiding on Image Encryption with Index Boundary for Partial Confidential Documents

2020 ◽  
Vol 8 (6) ◽  
pp. 3647-3650
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Vital Role ◽  
Cyber Attacks ◽  
Security Requirements ◽  
Digital Signals ◽  
Confidential Data ◽  
Efficient Data ◽  
Cyber Crimes ◽  
Arnold Transformation

An efficient data hiding method is proposed in the smart cyber-attacks such as data theft, virus attacks on the transmitting of whole confidential data, partial confidential data via private and government networks. The transmitting data over the internet is one of the better solutions to make a work easy and fast even though protecting data from the smart hackers is vital role in the cyber-crimes. There are various protection techniques of confidential data like digital watermarking, digital signals with embedding data into images, audio and videos. The existing watermarking techniques using RSA is a time consuming process for number of iterations to be performed even in signal decryption of image. These complexities of iterations to be overcome by the Least Significant Bits, DWT transformation and Arnold transformation were failing in all aspects of security requirements. The proposed method of reversible data hiding has an efficient encryption in medical images, health care image and data transmitting in various organizations.

A High Capacity Reversible Data Hiding Scheme for Halftone Images by Similar Pattern Selection

2012 ◽  
Vol 263-266 ◽  
pp. 2519-2523
Author(s):  
Mei Yi Wu ◽  
Jia Hong Lee
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Similar Pattern ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Pattern Selection ◽  
Data Embedding ◽  
Statistical Features ◽  
Encoding Scheme ◽  
Halftone Images

In this paper, we propose a high capacity reversible data hiding method for error diffused halftone images. It is a challenge to conceal data in halftone images due to their smaller depth. We utilize statistical features of pixel block patterns to embed data. The marked images can be perfectly reconstructed into their original halftone images. Traditional pair-based schemes selected two similar patterns as one pair to toggle one-bit data embedding. We extend the approaches and present a group-based encoding scheme to collect similar patterns into groups for multi-bits embedding. Experimental results show the proposed method can significantly improve the capacity of marked halftone images while preserve the similar marked image quality.

scholarly journals Code Division Multiplexing and Machine Learning Based Reversible Data Hiding Scheme for Medical Image

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Bin Ma ◽  
Bing Li ◽  
Xiao-Yu Wang ◽  
Chun-Peng Wang ◽  
Jian Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Medical Image ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Data Embedding ◽  
Secret Data ◽  
Spreading Sequences ◽  
Code Division Multiplexing

In this paper, a new reversible data hiding (RDH) scheme based on Code Division Multiplexing (CDM) and machine learning algorithms for medical image is proposed. The original medical image is firstly converted into frequency domain with integer-to-integer wavelet transform (IWT) algorithm, and then the secret data are embedded into the medium frequency subbands of medical image robustly with CDM and machine learning algorithms. According to the orthogonality of different spreading sequences employed in CDM algorithm, the secret data are embedded repeatedly, most of the elements of spreading sequences are mutually canceled, and the proposed method obtained high data embedding capacity at low image distortion. Simultaneously, the to-be-embedded secret data are represented by different spreading sequences, and only the receiver who has the spreading sequences the same as the sender can extract the secret data and original image completely, by which the security of the RDH is improved effectively. Experimental results show the feasibility of the proposed scheme for data embedding in medical image comparing with other state-of-the-art methods.

Reversible Data Hiding Based on Statistical Correlation of Blocked Sub-Sampled Image

2012 ◽  
Vol 2 (1) ◽  
pp. 42-59
Author(s):  
Mona Nafari ◽  
Mansour Nejati Jahromi ◽  
Gholam Hosein Sheisi
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Statistical Correlation ◽  
Experimental Results ◽  
Data Embedding ◽  
Embedding Capacity ◽  
Stego Image

In this paper, a reversible data hiding scheme has been proposed which is based on correlation of subsample images. The proposed method modifies the blocks of sub-sampled image to prepare vacant positions for data embedding. The PSNR of the stego image produced by the proposed method is guaranteed to be above 47.5 dB, while the embedding capacity is at least, almost 6.5 times higher than that of the Kim et al. techniques with the same PSNR. This technique has the capability to control the capacity-PSNR. Experimental results support that the proposed method exploits the correlation of blocked sub-sampled image outperforms the prior works in terms of larger capacity and stego image quality. On various test images, the authors demonstrate the validity of the proposed method by comparing it with other existing reversible data hiding algorithms.

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