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>

scholarly journals An analysis of the possibility of realization steganography in C#

2021 ◽  
Vol 21 ◽  
pp. 383-390
Author(s):  
Piotr Pawlak ◽  
Jakub Podgórniak ◽  
Grzegorz Kozieł
Keyword(s):  
Programming Language ◽  
Data Hiding ◽  
Digital Images ◽  
Secret Message ◽  
Optimal Solutions ◽  
Computing Power ◽  
C Language ◽  
C Programming Language ◽  
C Programming ◽  
Cryptographic Keys

The computing power of modern computers is sufficient to break many cryptographic keys, therefore it is necessary to create an additional security layer which hides the very fact of transmitting a secret message. For this purpose, steganographic methods can be used. The article is devoted to the analysis of the possibility of implementing digital images steganography with the use of the C # programming language. Firstly, existing libraries and mathematical transformations which can help with performing steganography were found. Also, own code solutions were implemented. In order to objectively evaluate the methods of data hiding, the parameters describing the degree of distortion of transforms and hidden images were calculated. Subsequently, optimal solutions for specific problems were identified and demonstrational data hiding was performed. Based on the obtained results, it can be concluded that it is possible to successfully implement steganography in the C # language. There are many ready-made libraries and tools, the effectiveness of which has been verified in the conducted analysis. Due to the contradictory of stenographic requirements, it is not possible to meet all of them optimally, i.e. undetectability, resistance to destruction and information capacity. For this reason, it is not possible to clearly indicate the best solutions. In order to achieve satisfactory results, one should look for compromises between the set requirements.

PVO-Based Multiple Message Segment Reversible Data Hiding

2019 ◽  
Vol 11 (1) ◽  
pp. 25-33
Author(s):  
Sahil Chhabra ◽  
Neeraj Kumar Jain ◽  
Vipin Tomar
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Digital Image ◽  
Reversible Data Hiding ◽  
Digital Images ◽  
Cover Image ◽  
Secret Message ◽  
Pixel Value ◽  
Digital Formats

In this article, a reversible data hiding technique is proposed to embed multiple segments of a single message into a single cover image. This multiple message segment technique uses a pixel value ordering approach to embed the secret message. The splitting and randomization of the original secret message provides security from an attacker There are many digital formats for data hiding, like images, audio, and video, of which the digital image is the simplest format. Data hiding in image processing refers to inserting the secret message into digital images. Reversible data hiding (RDH) is a lossless technique, in which both the embedded secret message and the cover image is extracted by the receiver. The applications of RDH include medical and military imaging.

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.

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 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.

Secure Data Transfer Using Image Steganography

2021 ◽  
Vol 9 (VIII) ◽  
pp. 175-180
Author(s):  
Nisha Manral
Keyword(s):  
Data Transfer ◽  
Digital Images ◽  
Image Steganography ◽  
Secret Message ◽  
The Internet ◽  
Secret Information ◽  
File Formats ◽  
Secure Data ◽  
Other Information ◽  
Weak Points

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the Internet. For hiding secret information in images, there exists a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Different applications have different requirements of the steganography technique used. For example, some applications may require absolute invisibility of the secret information, while others require a larger secret message to be hidden. This paper intends to give an overview of image steganography, its uses and techniques. It also attempts to identify the requirements of a good steganographic algorithm and briefly reflects on which steganographic techniques are more suitable for which applications.

A gradient based optimization procedure for finding axle weights in probabilistic bridge weigh-in-motion method

2020 ◽  
Author(s):  
Matheus Silva Gonçalves ◽  
Felipe Carraro ◽  
Rafael Holdorf Lopez
Keyword(s):  
Computational Complexity ◽  
Optimization Procedure ◽  
Grid Search ◽  
Original Algorithm ◽  
Influence Line ◽  
Weigh In Motion ◽  
Gradient Based ◽  
Bridge Weigh In Motion ◽  
Proposed Modification

Bridge weight in motion (BWIM) consists in the use of sensors on bridges to assess the loads of passing vehicles. Probabilistic Bridge Weight in Motion (pBWIM) is an approach for solving the inverse problem of finding vehicle axle weights based on deformation information. The pBWIM approach uses a probabilistic influence line and seeks the most probable axle weights, given in-situ measurements. To compute such weights, the original pBWIM employed a grid search, which may lead to computational complexity, specially when applied to vehicles with high number of axles. Hence, this note presents an improved version of pBWIM, modifying how the most probable weights are sough. Here, a gradient based optimization procedure is proposed for replacing the computationally expensive grid-search of the original algorithm. The required gradients are fully derived and validated in numerical examples. The proposed modification is shown to highly decrease the computational complexity of the problem.

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