New Data Hiding Algorithm in MATLAB Using Encrypted Secret Message

2011 ◽  
Author(s):  
Agniswar Dutta ◽  
Abhirup Kumar Sen ◽  
Sankar Das ◽  
Shalabh Agarwal ◽  
Asoke Nath
Keyword(s):  
Data Hiding ◽  
Secret Message

scholarly journals Efficient Reversible Data Hiding Scheme for AMBTC-Compressed Images

2021 ◽  
Vol 11 (15) ◽  
pp. 6741
Author(s):  
Chia-Chen Lin ◽  
Thai-Son Nguyen ◽  
Chin-Chen Chang ◽  
Wen-Chi Chang
Keyword(s):  
Data Hiding ◽  
Free Space ◽  
Reversible Data Hiding ◽  
Secret Message ◽  
Embedding Capacity ◽  
Absolute Moment ◽  
Compressed Images ◽  
High Embedding Capacity ◽  
Significant Attention ◽  
Efficiency Rate

Reversible data hiding has attracted significant attention from researchers because it can extract an embedded secret message correctly and recover a cover image without distortion. In this paper, a novel, efficient reversible data hiding scheme is proposed for absolute moment block truncation code (AMBTC) compressed images. The proposed scheme is based on the high correlation of neighboring values in two mean tables of AMBTC-compressed images to further losslessly encode these values and create free space for containing a secret message. Experimental results demonstrated that the proposed scheme obtained a high embedding capacity and guaranteed the same PSNRs as the traditional AMBTC algorithm. In addition, the proposed scheme achieved a higher embedding capacity and higher efficiency rate than those of some previous schemes while maintaining an acceptable bit rate.

scholarly journals A Distortion-Free Data Hiding Scheme for Triangular Meshes Based on Recursive Subdivision

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yuan-Yu Tsai
Keyword(s):  
Principal Component Analysis ◽  
Data Hiding ◽  
Similarity Transformation ◽  
Principal Component ◽  
Secret Message ◽  
Subdivision Scheme ◽  
Data Embedding ◽  
Embedding Capacity ◽  
Free Data ◽  
Reversible Data Embedding

This study adopts a triangle subdivision scheme to achieve reversible data embedding. The secret message is embedded into the newly added vertices. The topology of added vertex is constructed by connecting it with the vertices of located triangle. For further raising the total embedding capacity, a recursive subdivision mechanism, terminated by a given criterion, is employed. Finally, a principal component analysis can make the stego model against similarity transformation and vertex/triangle reordering attacks. Our proposed algorithm can provide a high and adjustable embedding capacity with reversibility. The experimental results demonstrate the feasibility of our proposed algorithm.

Fuzzy Proximity based Robust Data Hiding Scheme with Interval Threshold

2022 ◽  
Author(s):  
Prabhas Kumar Singh ◽  
Biswapati Jana ◽  
Kakali Datta
Keyword(s):  
Fuzzy Logic ◽  
Data Hiding ◽  
Processing System ◽  
Visual Quality ◽  
Structural Similarity ◽  
Secret Message ◽  
Secret Key ◽  
Post Processing ◽  
Coincidence Problem ◽  
Shared Secret

Abstract In 2020, Ashraf et al. proposed an interval type-2 fuzzy logic based block similarity calculation using color proximity relations of neighboring pixels in a steganographic scheme. Their method works well for detecting similarity, but it has drawbacks in terms of visual quality, imperceptibility, security, and robustness. Using Mamdani fuzzy logic to identify color proximity at the block level, as well as a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measure to ensure good visual quality, robustness, imperceptibility, and enhance the security. Further, the block color proximity is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. In order to increase the quality and accuracy of the recovered secret message, the tampering coincidence problem is solved through a post-processing approach. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.

A FPGA based Steganographic System Implementing a Modern Steganalysis Resistant LSB Algorithm

2017 ◽  
Vol 67 (5) ◽  
pp. 551 ◽  
Author(s):  
Kunjan Pathak ◽  
Manu Bansal
Keyword(s):  
Computational Complexity ◽  
Data Hiding ◽  
Hardware Implementation ◽  
Digital Images ◽  
Spatial Domain ◽  
Secret Message ◽  
Original Algorithm ◽  
Qualitative And Quantitative

<p>Steganography differs from other data hiding techniques because it encodes secret message inside cover object in such a way that transmission of secret message also remains a secret. Widespread usage of digital images, lower computational complexity and better performance makes spatial domain steganographic algorithms well suited for hardware implementation, which are not very frequent. This work tries to implement a modern steganalysis resistant LSB algorithm on FPGA based hardware. The presented work also optimises various operations and elements from original one third probability algorithm with respect to hardware implementation. The target FPGA for the implementation is Xilinx SP605 board (Spartan 6 series XC6SLX45T FPGA). Stego images obtained by the implementation have been thoroughly examined for various qualitative and quantitative aspects, which are found to be at par with original algorithm.</p>

Reversible data hiding method based on pixel expansion and homomorphic encryption

2020 ◽  
Vol 39 (3) ◽  
pp. 2977-2990
Author(s):  
R. Anushiadevi ◽  
Padmapriya Praveenkumar ◽  
John Bosco Balaguru Rayappan ◽  
Rengarajan Amirtharajan
Keyword(s):  
Image Quality ◽  
Data Hiding ◽  
Reversible Data Hiding ◽  
Signal To Noise Ratio ◽  
Homomorphic Encryption ◽  
Secret Message ◽  
Pixel Expansion ◽  
Stego Image ◽  
Encrypted Image ◽  
Location Map

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images.

scholarly journals Lossless and Reversible Data Hiding using Public Key Cryptography

2020 ◽  
Vol 32 ◽  
pp. 02002
Author(s):  
Pooja Shetye ◽  
Srushti Varekar ◽  
Manali Zajam ◽  
Monika Pawar ◽  
Sujata Kadam
Keyword(s):  
Data Hiding ◽  
Internet Access ◽  
Public Key Cryptography ◽  
Secret Message ◽  
Major Drawback ◽  
Plain Text ◽  
Private Key ◽  
Aes Algorithm ◽  
Cipher Text ◽  
Encryption And Decryption

In today’s world, the internet is a platform, where large amount of data can be obtained and transferred. Different technologies and internet access are used to transfer the data which can be accessed by authorized and unauthorized users.The major drawback of these technologies are that any unauthorized person can access it.Hence encryption and decryption is perform on Message/Data .In encryption the plain text/image is converted into cipher text/image.The technique of data hiding is used to hide the data that has to be transferred from the source to the destination.The process involves insertion of secret message in the cover image which is encrypted with the help of AES algorithm. This algorithm generates public/private key. All this process can be performed in lossless and reversible manner.

scholarly journals FPGA based Data Hiding through Steganography

2020 ◽  
Vol 9 (1) ◽  
pp. 2042-2045
Keyword(s):  
Data Hiding ◽  
Field Programmable Gate Array ◽  
High Capacity ◽  
Cover Image ◽  
Secret Message ◽  
Stego Image ◽  
Key Factor ◽  
Field Programmable ◽  
Shared Information ◽  
Hidden Data

Nowadays, the information security has been the key factor in communications, computer systems, electronic commerce and data sharing. One of the well-known methods for procuring the security of shared information using carrier files is steganography. The carrier file can be discrete such as image, text, audio and video etc. Digital images are the most commonly used format among those due to the high capacity and availability frequency. The hidden data is stored in an indistinct carrier in image steganography, i.e the digital image is used as a cover image to mask the secret message known as stego image. Cryptography can be then adapted for increasing the security of the stego image. A zig-zag MSB-LSB slicing based steganographic algorithm is proposed in this paper for concealing a secret image in a cover image. Power report and device utilization summary of the algorithm is calculated and the output is demonstrated on the VGA screen using BASYS3 Field Programmable Gate Array (FPGA).

A Secure Data-Hiding Approach Using Particle Swarm Optimization and Pixel Value Difference

2016 ◽  
pp. 363-381
Author(s):  
Tanmoy Halder ◽  
Sunil Karforma ◽  
Rupali Halder
Keyword(s):  
Particle Swarm Optimization ◽  
Data Hiding ◽  
Particle Swarm ◽  
Secret Message ◽  
Secret Data ◽  
Swarm Optimization ◽  
Pixel Value ◽  
The Difference ◽  
Block Based ◽  
Pixel Value Difference

In this chapter a novel data hiding approach by combining Particle Swarm Optimization (PSO) and Pixel Value Difference (PVD) has been proposed. Pixel-Value-Difference (PVD) method of Steganography uses the difference between pixels within an image to hide secret data. The proposed method is a block-based adaptive steganographic approach, which selects M×N block of pixels from cover image and embed secret message within pixels using Pixel-value-difference and LSB substitution method. PSO is used to select most appropriate areas within the image for hiding secret information. Results obtained using the approach show that distortion due to data embedding is negligible. The proposed approach is compared with existing methods in terms of bits per pixel. This method could be applied to hide any digital secret data for secure transfer over internet.

An Overview of Steganography

2017 ◽  
pp. 116-144
Author(s):  
Al Hussien Seddik Saad ◽  
Abdelmgeid Amin Ali
Keyword(s):  
Data Hiding ◽  
Secret Message ◽  
System Evaluation ◽  
The Internet ◽  
Historical Events ◽  
Important Data ◽  
Open Environment ◽  
Video Images ◽  
System Requirements

Nowadays, due to the increasing need for providing secrecy in an open environment such as the internet, data hiding has been widely used. Steganography is one of the most important data hiding techniques which hides the existence of the secret message in cover files or carriers such as video, images, audio or text files. In this chapter; steganography will be introduced, some historical events will be listed, steganography system requirements, categories, classifications, cover files will be discussed focusing on image and video files, steganography system evaluation, attacks, applications will be explained in details and finally last section concludes the chapter.

scholarly journals Reversible Data Hiding Based on Image Interpolation with a Secret Message Reduction Strategy

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Tzu-Chuen Lu ◽  
Mei-Chen Lin ◽  
Chun-Chih Huang ◽  
Kuang-Mao Deng
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
Image Interpolation ◽  
Secret Message ◽  
Reduction Strategy
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