An information theoretic image steganalysis for LSB steganography

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. I...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Chhikara Sonam
Kumar Rajeev
Dokumentumtípus: Cikk
Megjelent: University of Szeged, Institute of Informatics Szeged 2020
Sorozat:Acta cybernetica 24 No. 4
Kulcsszavak:Szteganográfia, Információelmélet, Kibernetika
Tárgyszavak:
doi:10.14232/actacyb.279174

Online Access:http://acta.bibl.u-szeged.hu/71766
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245 1 3 |a An information theoretic image steganalysis for LSB steganography  |h [elektronikus dokumentum] /  |c  Chhikara Sonam 
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490 0 |a Acta cybernetica  |v 24 No. 4 
520 3 |a 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. 
650 4 |a Természettudományok 
650 4 |a Számítás- és információtudomány 
695 |a Szteganográfia, Információelmélet, Kibernetika 
700 0 1 |a Kumar Rajeev  |e aut 
856 4 0 |u http://acta.bibl.u-szeged.hu/71766/1/cybernetica_024_numb_004_593-612.pdf  |z Dokumentum-elérés