An information theoretic image steganalysis for LSB steganography

Chhikara Sonam and Kumar Rajeev: An information theoretic image steganalysis for LSB steganography. In: Acta cybernetica, (24) 4. pp. 593-612. (2020)

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Abstract

Steganography hides the data within a media file in an imperceptible way. Steganalysis exposes steganography by using detection measures. Traditionally, Steganalysis revealed steganography by targeting perceptible and statistical properties which results in developing secure steganography schemes. In this work, we target LSB image steganography by using entropy and joint entropy metrics for steganalysis. First, the Embedded image is processed for feature extraction then analyzed by entropy and joint entropy with their corresponding original image. Second, SVM and Ensemble classifiers are trained according to the analysis results. The decision of classifiers discriminates cover image from stego image. This scheme is further applied on attacked stego image for checking detection reliability. Performance evaluation of proposed scheme is conducted over grayscale image datasets. We analyzed LSB embedded images by Comparing information gain from entropy and joint entropy metrics. Results conclude that entropy of the suspected image is more preserving than joint entropy. As before histogram attack, detection rate with entropy metric is 70% and 98% with joint entropy metric. However after an attack, entropy metric ends with 30% detection rate while joint entropy metric gives 93% detection rate. Therefore, joint entropy proves to be better steganalysis measure with 93% detection accuracy and less false alarms with varying hiding ratio.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2020
Volume: 24
Number: 4
ISSN: 0324-721X
Page Range: pp. 593-612
Language: English
Publisher: University of Szeged, Institute of Informatics
Place of Publication: Szeged
Related URLs: http://acta.bibl.u-szeged.hu/71734/
DOI: 10.14232/actacyb.279174
Uncontrolled Keywords: Szteganográfia, Információelmélet, Kibernetika
Additional Information: Bibliogr.: p. 610-612. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
Date Deposited: 2021. Feb. 05. 11:47
Last Modified: 2022. Jun. 21. 09:20
URI: http://acta.bibl.u-szeged.hu/id/eprint/71766

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