Paper Info
Title
A differential evolution based algorithm for breaking the visual steganalytic system
Abstract
Image steganography is the process of sending messages secretly by hiding the message in image content. Steganalytic techniques are used to detect whether an image contains a hidden message by analyzing various image features between stego-images (the images containing hidden messages) and cover-images (the images containing no hidden messages). In the past, genetic algorithm (GA) was applied to design a robust steganographic system that breaks the steganalytic systems. However, GA consumes too much time to converge to the optimal solution. In this paper, we use a different evolutionary approach, named differential evolution (DE), to increase the performance of the steganographic system. The key element that DE is distinguished from other population based approaches is differential mutation, which aims to find the global optimum of a multidimensional, multimodal function. Experimental results show that the application of the DE based steganography not only improves the peak signal to noise ratio (PSNR) of the stego-image, but also promotes the normalized correlation (NC) of the extracted secret message for the same number of iterations. It is observed that the percentage increase in PSNR values ranges from 5% to 13% and that of NC values ranges from 0.8% to 3%.
Year
DOI
Venue
2009
10.1007/s00500-008-0330-z
Soft Comput.
Keywords
Field
DocType
various image feature,steganography · steganalysis · watermarking · differential evolution · genetic algorithm,visual steganalytic system,image content,hidden message,percentage increase,image steganography,steganalytic system,differential evolution,differential mutation,secret message,robust steganographic system,genetic algorithm,image features,peak signal to noise ratio
Population,Peak signal-to-noise ratio,Steganography,Digital watermarking,Feature (computer vision),Computer science,Algorithm,Differential evolution,Theoretical computer science,Steganalysis,Genetic algorithm
Journal
Volume
Issue
ISSN
13
4
1433-7479
Citations 
PageRank 
References 
7
0.45
7
Authors
2
Name
Order
Citations
PageRank
Frank Y. Shih1110389.56
Venkata Gopal Edupuganti270.79