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EA based Heuristic Segmentation for Efficient Data Hiding

by Raniyah Abdullah Wazirali, Zenon Chaczko
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 5
Year of Publication: 2015
Authors: Raniyah Abdullah Wazirali, Zenon Chaczko
10.5120/20738-3126

Raniyah Abdullah Wazirali, Zenon Chaczko . EA based Heuristic Segmentation for Efficient Data Hiding. International Journal of Computer Applications. 118, 5 ( May 2015), 1-7. DOI=10.5120/20738-3126

@article{ 10.5120/20738-3126,
author = { Raniyah Abdullah Wazirali, Zenon Chaczko },
title = { EA based Heuristic Segmentation for Efficient Data Hiding },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 5 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number5/20738-3126/ },
doi = { 10.5120/20738-3126 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:00:50.813662+05:30
%A Raniyah Abdullah Wazirali
%A Zenon Chaczko
%T EA based Heuristic Segmentation for Efficient Data Hiding
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 5
%P 1-7
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Information concealment is of paramount importance in information and communication security. For the protection of information and intellectual property, effective techniques are needed. Steganography is the art of writing concealed information in a way that it does not arouse suspicion about its existence. This ensures that only the sender and the recipient are aware of the concealed message existence. Capacity and Stego image imperceptibility are the most crucial aspects. This paper provides a heuristic approach of choosing the right-most regions for embedding that ensure minimum changes to stego object. Then, different percentages of secret data will be hidden on the cluster based on the characteristic of the region. Therefore, the sharp edge region will hide more data while the smooth will hide data. The proposed approach use K-mean clustering to categorized the segmentation and then genetic algorithm will be used to boost the PSNR (peak signal to-noise ratio) value while optimizing high capacity information. The obtained stego object is virtually indistinguishable from the cover object. The experimental results show a significant enhancement over other previous work.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Steganography LSB K-mean clustering GA

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