A graph–theoretic approach to steganography
Stefan Hetzl,Petra Mutzel +1 more
- pp 119-128
TLDR
A graph-theoretic approach to steganography based on the idea of exchanging rather than overwriting pixels is suggested and an algorithm based on this approach with support for several types of image and audio files is implemented.Abstract:
We suggest a graph-theoretic approach to steganography based on the idea of exchanging rather than overwriting pixels. We construct a graph from the cover data and the secret message. Pixels that need to be modified are represented as vertices and possible partners of an exchange are connected by edges. An embedding is constructed by solving the combinatorial problem of calculating a maximum cardinality matching. The secret message is then embedded by exchanging those samples given by the matched edges. This embedding preserves first-order statistics. Additionally, the visual changes can be minimized by introducing edge weights.
We have implemented an algorithm based on this approach with support for several types of image and audio files and we have conducted computational studies to evaluate the performance of the algorithm.read more
Citations
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Journal ArticleDOI
Steganalysis by Subtractive Pixel Adjacency Matrix
TL;DR: A method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching.
Book
Steganography in Digital Media: Principles, Algorithms, and Applications
TL;DR: This clear, self-contained guide shows you how to understand the building blocks of covert communication in digital media files and how to apply the techniques in practice, including those of steganalysis, the detection of Steganography.
Proceedings ArticleDOI
Merging Markov and DCT Features for Multi-Class JPEG Steganalysis
Tomas Pevny,Jessica Fridrich +1 more
TL;DR: In this article, a support vector machine (SVM) was used to construct a new multi-class JPEG steganalyzer with markedly improved performance by extending the 23 DCT feature set and applying calibration to the Markov features.
Proceedings ArticleDOI
Statistically undetectable jpeg steganography: dead ends challenges, and opportunities
TL;DR: The goal of this paper is to determine the steganographic capacity of JPEG images (the largest payload that can be undetectably embedded) with respect to current best steganalytic methods and to evaluate the influence of specific design elements and principles.
Proceedings ArticleDOI
Steganalysis by subtractive pixel adjacency matrix
TL;DR: A method for detection of steganographic methods that embed in the spatial domain by adding a low-amplitude independent stego signal, an example of which is least significant bit (LSB) matching.
References
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