Cover Image

PSW statistical LSB image steganalysis

Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art and science of detecting the existence of these. This manuscript proposes a novel blind statistical steganalysis technique to detect Least...

Full description

Saved in:
Bibliographic Details
Main Authors: Shojae Chaeikar, Saman, Zamani, Mazdak, Abdul Manaf, Azizah, Zeki, Akram M.
Format: Article
Language:English
English
Published: Springer New York LLC 2017
Subjects:
T Technology (General)
Online Access:http://irep.iium.edu.my/62992/19/62992_PSW%20statistical%20LSB%20image%20steganalysis_article.pdf
http://irep.iium.edu.my/62992/8/62992_PSW%20statistical%20LSB%20image%20steganalysis_scopus.pdf
http://irep.iium.edu.my/62992/
https://srv2.freepaper.me/n/_eHfQjpkHelC2u-rnm8IoA/PDF/52/5289c9e1b0bbe31dca4edd53a138bf55.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.iium.irep.62992
record_format dspace
spelling my.iium.irep.629922019-07-12T08:42:53Z http://irep.iium.edu.my/62992/ PSW statistical LSB image steganalysis Shojae Chaeikar, Saman Zamani, Mazdak Abdul Manaf, Azizah Zeki, Akram M. T Technology (General) Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art and science of detecting the existence of these. This manuscript proposes a novel blind statistical steganalysis technique to detect Least Significant Bit (LSB) flipping image steganography. It shows that the technique has a number of major advantages. First, a novel method of pixel color correlativity analysis in Pixel Similarity Weight (PSW). Second, filtering out image pixels according to their statistically detected suspiciousness, thereby excluding neutral pixels from the steganalysis process. Third, ranking suspicious pixels according to their statistically detected suspiciousness and determining the influence of such pixels based on the level of detected anomalies. Fourth, the capability to classify and analyze pixels in three pixel classes of flat, smooth and edgy, thereby enhancing the sensitivity of the steganalysis. Fifth, achieving an extremely high efficiency level of 98.049% in detecting 0.25bpp stego images with only a single dimension analysis. Springer New York LLC 2017-01-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/62992/19/62992_PSW%20statistical%20LSB%20image%20steganalysis_article.pdf application/pdf en http://irep.iium.edu.my/62992/8/62992_PSW%20statistical%20LSB%20image%20steganalysis_scopus.pdf Shojae Chaeikar, Saman and Zamani, Mazdak and Abdul Manaf, Azizah and Zeki, Akram M. (2017) PSW statistical LSB image steganalysis. Multimedia Tools and Applications, 77 (1). pp. 805-835. ISSN 1380-7501 https://srv2.freepaper.me/n/_eHfQjpkHelC2u-rnm8IoA/PDF/52/5289c9e1b0bbe31dca4edd53a138bf55.pdf 10.1007/s11042-016-4273-6
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Shojae Chaeikar, Saman
Zamani, Mazdak
Abdul Manaf, Azizah
Zeki, Akram M.
PSW statistical LSB image steganalysis
description Steganography is the art and science of producing covert communications by concealing secret messages in apparently innocent media, while steganalysis is the art and science of detecting the existence of these. This manuscript proposes a novel blind statistical steganalysis technique to detect Least Significant Bit (LSB) flipping image steganography. It shows that the technique has a number of major advantages. First, a novel method of pixel color correlativity analysis in Pixel Similarity Weight (PSW). Second, filtering out image pixels according to their statistically detected suspiciousness, thereby excluding neutral pixels from the steganalysis process. Third, ranking suspicious pixels according to their statistically detected suspiciousness and determining the influence of such pixels based on the level of detected anomalies. Fourth, the capability to classify and analyze pixels in three pixel classes of flat, smooth and edgy, thereby enhancing the sensitivity of the steganalysis. Fifth, achieving an extremely high efficiency level of 98.049% in detecting 0.25bpp stego images with only a single dimension analysis.
format Article
author Shojae Chaeikar, Saman
Zamani, Mazdak
Abdul Manaf, Azizah
Zeki, Akram M.
author_facet Shojae Chaeikar, Saman
Zamani, Mazdak
Abdul Manaf, Azizah
Zeki, Akram M.
author_sort Shojae Chaeikar, Saman
title PSW statistical LSB image steganalysis
title_short PSW statistical LSB image steganalysis
title_full PSW statistical LSB image steganalysis
title_fullStr PSW statistical LSB image steganalysis
title_full_unstemmed PSW statistical LSB image steganalysis
title_sort psw statistical lsb image steganalysis
publisher Springer New York LLC
publishDate 2017
url http://irep.iium.edu.my/62992/19/62992_PSW%20statistical%20LSB%20image%20steganalysis_article.pdf
http://irep.iium.edu.my/62992/8/62992_PSW%20statistical%20LSB%20image%20steganalysis_scopus.pdf
http://irep.iium.edu.my/62992/
https://srv2.freepaper.me/n/_eHfQjpkHelC2u-rnm8IoA/PDF/52/5289c9e1b0bbe31dca4edd53a138bf55.pdf
_version_ 1643619704321867776
score 13.211869

Similar Items