High-Payload Data-Hiding Method for AMBTC Decompressed Images

Data hiding is the art of embedding data into a cover image without any perceptual distortion of the cover image. Moreover, data hiding is a very crucial research topic in information security because it can be used for various applications. In this study, we proposed a high-capacity data-hiding scheme for absolute moment block truncation coding (AMBTC) decompressed images. We statistically analyzed the composition of the secret data string and developed a unique encoding and decoding dictionary search for adjusting pixel values. The dictionary was used in the embedding and extraction stages. The dictionary provides high data-hiding capacity because the secret data was compressed using dictionary-based coding. The experimental results of this study reveal that the proposed scheme is better than the existing schemes, with respect to the data-hiding capacity and visual quality.

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Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3701.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 11473-11478

Keyword(s):

Data Hiding ◽

Enhanced Recovery ◽

Signal To Noise Ratio ◽

Image Steganography ◽

Cover Image ◽

Mapping Technique ◽

Secret Data ◽

Logical Function ◽

Hiding Capacity ◽

Carrier Image

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.

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A Novel Method for High Capacity Reversible Data Hiding Scheme Using Difference Expansion

International Journal of Natural Computing Research ◽

10.4018/ijncr.2019100102 ◽

2019 ◽

Vol 8 (4) ◽

pp. 13-27

Author(s):

Subhadip Mukherjee ◽

Biswapati Jana

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

Data Extraction ◽

High Capacity ◽

Correlation Coefficients ◽

Extraction Process ◽

Research Area ◽

Difference Expansion ◽

Secret Data ◽

Hiding Capacity

Data hiding techniques are very significant in the research area of information security. In this article, the authors propose a new reversible data hiding (RDH) scheme using difference expansion. At first, the original image is partitioned into 3 × 3 pixel blocks, then marked Type-one and Type-two pixels based on their coordinate values. After that, the authors find correlated pixels by computing correlation coefficients and the median of Type-one pixels. Next, secret data bits are embedded within Type-two pixels based on correlated pixels and Type-one pixels based on the stego Type-two pixels. The data extraction process successfully extracts secret data as well as recovers the cover image. The authors observed the effects of the proposed method by performing experiments on some standard cover images and found significantly better result in terms of data hiding capacity compared with existing data hiding schemes.

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A Reversible High-Capacity Data Hide System Based on Powerful MSB Prediction in Encrypted Images

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.a2370.059120 ◽

2020 ◽

Vol 9 (1) ◽

pp. 1388-1390

Keyword(s):

Data Hiding ◽

Data Privacy ◽

High Capacity ◽

Embedding Efficiency ◽

Additional Information ◽

Encrypted Images ◽

Original Picture ◽

Capacity Data ◽

Very High ◽

Better Than

For encrypted images (RDHEI) reversible data shielding is an important technique for embedding data into the encrypted domain. A hidden key encrypts an original picture, and additional information may be inserted into the encrypted image during or after transmission without knowing the crypting key or the original contents of the picture. The hidden message can be retrieved during the decoding process and the original image can be restored. RDHEI has begun to generate academic attention over the past couple of years. Data privacy has become a real issue with the growth of cloud computing. None of the current methods, however, will allow us to hide a great deal of information reversibly. In this document we propose a new reversible approach with a very high capacity based on MSB (most important bit) forecasting. We present two approaches: a reversible high-capacity data hiding approach with a prediction-correction error (CPEHCRDH) and an integrated-prediction error (EPE-HCRDH) reversible data hiding approach. With this approach, our findings are better than those achieved with the existing state-of-the-art approaches, both in terms of image quality recovered and embedding efficiency.

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Improved Encrypted-Signals-Based Reversible Data Hiding Using Code Division Multiplexing and Value Expansion

Security and Communication Networks ◽

10.1155/2018/1326235 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Xianyi Chen ◽

Haidong Zhong ◽

Lizhi Xiong ◽

Zhihua Xia

Keyword(s):

Data Hiding ◽

Reversible Data Hiding ◽

High Capacity ◽

Signal Energy ◽

Spreading Sequence ◽

Capacity Data ◽

Embedding Rate ◽

Better Than ◽

Code Division Multiplexing

Compared to the encrypted-image-based reversible data hiding (EIRDH) method, the encrypted-signals-based reversible data hiding (ESRDH) technique is a novel way to achieve a greater embedding rate and better quality of the decrypted signals. Motivated by ESRDH using signal energy transfer, we propose an improved ESRDH method using code division multiplexing and value expansion. At the beginning, each pixel of the original image is divided into several parts containing a little signal and multiple equal signals. Next, all signals are encrypted by Paillier encryption. And then a large number of secret bits are embedded into the encrypted signals using code division multiplexing and value expansion. Since the sum of elements in any spreading sequence is equal to 0, lossless quality of directly decrypted signals can be achieved using code division multiplexing on the encrypted equal signals. Although the visual quality is reduced, high-capacity data hiding can be accomplished by conducting value expansion on the encrypted little signal. The experimental results show that our method is better than other methods in terms of the embedding rate and average PSNR.

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A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189877 ◽

2021 ◽

pp. 1-11

Author(s):

Kusan Biswas

Keyword(s):

Data Hiding ◽

High Capacity ◽

Error Correcting Codes ◽

Human Vision ◽

Data Embedding ◽

Compressed Images ◽

Matrix Encoding ◽

Dct Coefficients ◽

Capacity Data ◽

Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

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A novel steganographic methodology for high capacity data hiding in executable files

International Journal of Internet Technology and Secured Transactions ◽

10.1504/ijitst.2011.039779 ◽

2011 ◽

Vol 3 (2) ◽

pp. 210

Author(s):

Rajesh Kumar Tiwari ◽

G. Sahoo

Keyword(s):

Data Hiding ◽

High Capacity ◽

Capacity Data

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A Location Map Reduced Reversible Data Hiding Method Using Prediction Error Modification

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.6-7.428 ◽

2012 ◽

Vol 6-7 ◽

pp. 428-433

Author(s):

Yan Wei Li ◽

Mei Chen Wu ◽

Tung Shou Chen ◽

Wien Hong

Keyword(s):

Image Quality ◽

Data Hiding ◽

Prediction Error ◽

Reversible Data Hiding ◽

Experimental Results ◽

Cover Image ◽

Prediction Errors ◽

Secret Data ◽

Location Map ◽

Comparable Image Quality

We propose a reversible data hiding technique to improve Hong and Chen’s (2010) method. Hong and Chen divide the cover image into pixel group, and use reference pixels to predict other pixel values. Data are then embedded by modifying the prediction errors. However, when solving the overflow and underflow problems, they employ a location map to record the position of saturated pixels, and these pixels will not be used to carry data. In their method, if the image has a plenty of saturated pixels, the payload is decreased significantly because a lot of saturated pixels will not joint the embedment. We improve Hong and Chen’s method such that the saturated pixels can be used to carry data. The positions of these saturated pixels are then recorded in a location map, and the location map is embedded together with the secret data. The experimental results illustrate that the proposed method has better payload, will providing a comparable image quality.

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High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift

Security and Communication Networks ◽

10.1155/2018/2029869 ◽

2018 ◽

Vol 2018 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Dinh-Chien Nguyen ◽

Thai-Son Nguyen ◽

Chin-Chen Chang ◽

Huan-Sheng Hsueh ◽

Fang-Rong Hsu

Keyword(s):

Digital Media ◽

Data Hiding ◽

Video Sequences ◽

Embedding Capacity ◽

Secret Data ◽

Low Distortion ◽

High Embedding Capacity ◽

Advanced Video Coding ◽

Distortion Drift ◽

Capacity Data

Data hiding is a technique that allows secret data to be delivered securely by embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high embedding capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of I frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the embedding group and the averting group. The embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced embedding capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.

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