scholarly journals ACO Based Variable Least Significant Bits Data Hiding in Edges Using IDIBS Algorithm

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 781
Author(s):  
Sahib Khan ◽  
Muhammad Abeer Irfan ◽  
Khalil Khan ◽  
Mushtaq Khan ◽  
Tawab Khan ◽  
...  
Keyword(s):  
Data Hiding ◽  
Cover Image ◽  
Hidden Information ◽  
Secret Data ◽  
High Quality ◽  
Complex Region ◽  
Asymmetric Data ◽  
Smooth Region ◽  
Least Significant Bits

This work presents a double asymmetric data hiding technique. The first asymmetry is created by hiding secret data in the complex region of the cover image and keep the smooth region unaffected. Then another asymmetry is developed by hiding a different number of secret bits in the various pixels of the complex region. The proposed technique uses the ant colony optimization (ACO) based technique for the classification of complex and smooth region pixels. Then, the variable least significant bits (VLSB) data hiding framework is used to hide secret bits in the complex region of the cover image. A distance-based substitution technique, namely increasing distance increasing bits substitution algorithm, is used to ensure the asymmetry in the number of hidden bits. The double asymmetric framework enhances the security of the hidden secret data and makes the retrieval of hidden information difficult for unauthorized users. The algorithm results in high-quality stego images, and the hidden information does not attract the human visual system (HVS).

scholarly journals Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region

2018 ◽  
Vol 8 (1) ◽  
pp. 379 ◽  
Author(s):  
Sahib Khan
Keyword(s):  
Ant Colony Optimization ◽  
Data Hiding ◽  
Experimental Results ◽  
Ant Colony ◽  
Cover Image ◽  
Complex Region ◽  
Secret Information ◽  
Lsb Substitution ◽  
Least Significant Bits

This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method.

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

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.

scholarly journals High-Payload Data-Hiding Method for AMBTC Decompressed Images

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 145
Author(s):  
Jung-Yao Yeh ◽  
Chih-Cheng Chen ◽  
Po-Liang Liu ◽  
Ying-Hsuan Huang
Keyword(s):  
Data Hiding ◽  
High Capacity ◽  
Cover Image ◽  
Secret Data ◽  
Perceptual Distortion ◽  
Hiding Capacity ◽  
High Data ◽  
Capacity Data ◽  
High Payload ◽  
Better Than

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.

scholarly journals Reversible data hiding scheme based on pixel-value differencing in dual images

2020 ◽  
Vol 16 (7) ◽  
pp. 155014772091100
Author(s):  
Pyung-Han Kim ◽  
Kwan-Woo Ryu ◽  
Ki-Hyun Jung
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Data Extraction ◽  
Cover Image ◽  
Maximum Difference ◽  
Secret Data ◽  
Pixel Value ◽  
The Difference ◽  
Pixel Value Differencing ◽  
Dual Images

In this article, a new reversible data hiding scheme using pixel-value differencing in dual images is proposed. The proposed pixel-value differencing method can embed more secret data as the difference value of adjacent pixels is increased. In the proposed scheme, the cover image is divided into non-overlapping blocks and the maximum difference value is calculated to hide secret bits. On the sender side, the length of embeddable secret data is calculated by using the maximum difference value and the log function, and the decimal secret data are embedded into the two stego-images after applying the ceil function and floor function. On the receiver side, the secret data extraction and the cover image restoration can be performed by using the correlation between two stego-images. After recovering the cover image from two stego-images, the secret data can be extracted using the maximum difference value and the log function. The experimental results show that the proposed scheme has a higher embedding capacity and the proposed scheme differs in embedding the secret data depending on the characteristics of the cover image with less distortion. Also, the proposed scheme maintains the degree of image distortion that cannot be perceived by the human visual system.

An Efficient Reversible Data Hiding Scheme for Encrypted Images

2018 ◽  
Vol 10 (2) ◽  
pp. 1-22 ◽  
Author(s):  
Kai Chen ◽  
Dawen Xu
Keyword(s):  
Data Hiding ◽  
Efficient Method ◽  
Reversible Data Hiding ◽  
Additional Data ◽  
Emerging Technology ◽  
Experimental Results ◽  
Cover Image ◽  
Original Image ◽  
Secret Data ◽  
Encrypted Images

Reversible data hiding in the encrypted domain is an emerging technology, as it can preserve the confidentiality. In this article, an efficient method of reversible data hiding in encrypted images is proposed. The cover image is first partitioned into non-overlapping blocks. A specific modulo addition operation and block-scrambling operation are applied to obtain the encrypted image. The data-hider, who does not know the original image content, may reversibly embed secret data based on the homomorphic property of the cryptosystem. A scale factor is utilized for selecting embedding zone, which is scalable for different capacity requirements. At the receiving end, the additional data can be extracted if the receiver has the data-hiding key only. If the receiver has the encryption key only, he/she can recover the original image approximately. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original content without any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

scholarly journals Improved Data Hiding Scheme using VQ based Index Map Compression and Codebook Extension

2020 ◽  
Vol 9 (5) ◽  
pp. 801-807
Keyword(s):  
Vector Quantization ◽  
Data Hiding ◽  
Cover Image ◽  
Embedding Capacity ◽  
Text File ◽  
Secret Data ◽  
Video File ◽  
Coding Efficiency ◽  
Confidential Data ◽  
The Cost

Now-a-days, data protection has become inevitable for confidential transactions that happen over net. Transmission of such confidential data has become a challenging issue in today’s scenario. Many Data Hiding techniques are used for transmitting data in a secured way. The secret data can be hidden as part of any type of file such as Text file, Sound file, image file, Video file, etc. It has been proposed to hide secret data as part of cover image. The proposed work adopts Vector Quantization (VQ) which is one of the powerful and simple image compression techniques to compress the size of the cover image and to reduce the cost associated with storage/transmission. VQ transforms the cover image into its corresponding Codebook and IndexMap. The confidential data is then embedded as part of the Codebook and IndexMap. The proposed method helps in improving the performance by increasing the embedding capacity and coding efficiency. The performance of Steganography is improved in three levels. The embedding capacity of the proposed method is increased by 23,726 bits when compared to that of existing similar methods, which is a significant improvement.

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

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.

Block-Based Reversible Data Hiding Using Histogram Shifting and Modulus Operator for Digital Images

2017 ◽  
Vol 26 (06) ◽  
pp. 1750103 ◽  
Author(s):  
Pankaj Garg ◽  
Singara Singh Kasana ◽  
Geeta Kasana
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Cover Image ◽  
Histogram Shifting ◽  
Embedding Capacity ◽  
Signal To Noise ◽  
Secret Data ◽  
Peak Points ◽  
Block Based

A Reversible Data Hiding technique by using histogram shifting and modulus operator is proposed in which secret data is embedded into blocks of the cover image. These blocks are modified by using modulus operator to increase the number of peak points in the histogram of the cover image which further increases its embedding capacity. Secret data is embedded in the original cover blocks of the cover image by using peak points of the predicted blocks, which are generated by using modulus operator. Peak Signal to Noise Ratio and PSNR-Human Visual System are used to show the human visual acceptance of the proposed technique. Experimental results show that the embedding capacity is high as compared to the capacity of existing RDH techniques, while distortion in marked images is also less as compared to distortion produced by these existing techniques.

scholarly journals Secret data sharing using steganography and image processing

2018 ◽  
Vol 7 (1.7) ◽  
pp. 100 ◽  
Author(s):  
R Bhuvanya ◽  
K Vijayalakshmi ◽  
S Uma ◽  
A A.Suresh
Keyword(s):  
Image Processing ◽  
Data Sharing ◽  
Implementation Process ◽  
Cover Image ◽  
Hidden Information ◽  
Secret Data ◽  
Stego Image ◽  
Distortion Functions ◽  
Password Protection ◽  
Additive Distortion

Steganography is a technique that helps to hide the secret data inside the digitally covered image. The message to be hidden can be a text,image, speech, video. The proposed method aims to combine the technique of steganography and Image Processing. Cover image helps to carry the secret data in an embedded form which is referred as stego image. This work proposes a new implementation process called clustering modification directions (CMDs). To implement this methodology, several sub images will be created by decomposing the cover image using additive distortion functions. To enhance the security, password protection is also applied for the hidden information to be retrieved.

Robust data hiding with multiple backups and optimized reference matrix

2020 ◽  
Vol 39 (5) ◽  
pp. 6965-6977
Author(s):  
Xianquan Zhang ◽  
Ju Yang ◽  
Yu Dong ◽  
Chunqiang Yu ◽  
Zhenjun Tang
Keyword(s):  
Data Hiding ◽  
Data Extraction ◽  
Experimental Results ◽  
Cover Image ◽  
Secret Data ◽  
Stego Image ◽  
Group Data ◽  
Reference Matrix

Most data hiding methods have limitations in resisting cropping and noise attacks. Aiming at this problem, a robust data hiding with multiple backups and optimized reference matrix is proposed in this paper. Specifically, secret data is divided into a set of groups and multiple backups of each group data are generated according to the number of backups. The cover image is divided into several blocks. A reference matrix is constructed by four constraints to assist data hiding and data extraction. The proposed method aims to extract exactly at least one backup of each group data so that the correct backups can construct the secret data well if the stego-image is corrupted. Experimental results show that the proposed algorithm is robust to cropping and noise attacks.

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