A stylometry approach for blind linguistic steganalysis model against translation-based steganography

Steganography is the art of hiding information in ways that prevent the detection of a secret message. In Translation-based Steganography (TBS), the secret messages are encoded in the “noise” made via translation of natural language text programmed. The adversarial technique to extract the secret me...

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Main Author:	Mohd Lokman, Syiham
Format:	Thesis
Language:	English English English
Published:	2023
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/10995/1/24p%20SYIHAM%20MOHD%20LOKMAN.pdf http://eprints.uthm.edu.my/10995/2/SYIHAM%20MOHD%20LOKMAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10995/3/SYIHAM%20MOHD%20LOKMAN%20WATERMARK.pdf
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spelling	my-uthm-ep.109952024-05-20T01:36:54Z A stylometry approach for blind linguistic steganalysis model against translation-based steganography 2023-02 Mohd Lokman, Syiham T Technology (General) Steganography is the art of hiding information in ways that prevent the detection of a secret message. In Translation-based Steganography (TBS), the secret messages are encoded in the “noise” made via translation of natural language text programmed. The adversarial technique to extract the secret message is called steganalysis, which can be categorized into two types; targeted vs. blind. While targeted steganalysis is designed to attack a specific embedding algorithm, blind steganalysis use features extracted or selection from the medium to detect any anomalies that indicate a possibility that a secret data has been embedded within the medium. However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. This thesis explore the potential of using stylometry or linguistic style to improve the representation of characteristics among the word distribution in distinguishing the stego text from the cover text for TBS. This is because all translated in TBS text have an intrinsic structural styles that can be used to improve the performance of a blind steganalysis model. The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. The proposed stylometric features selected from a set of cover text are categorized into two group features; lexical and syntactic features before implemented into the model Support Vector Machine (SVM) as the classifier. The performance of the stylometry-based blind steganalysis model is then evaluated based on all false rate, missing rate and accuracy rate and compared against three other standard classifiers in steganalysis; Naive Bayes (NB), k-Nearest Neighbor (k-NN), and Decision Tree (J48). The results showed that the stylometric features are impactful to a blind steganalysis model by giving higher detection performance. Meanwhile, SVM is the best classifier for stego text detection with significantly low processing time performance 2023-02 Thesis http://eprints.uthm.edu.my/10995/ http://eprints.uthm.edu.my/10995/1/24p%20SYIHAM%20MOHD%20LOKMAN.pdf text en public http://eprints.uthm.edu.my/10995/2/SYIHAM%20MOHD%20LOKMAN%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/10995/3/SYIHAM%20MOHD%20LOKMAN%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Mohd Lokman, Syiham A stylometry approach for blind linguistic steganalysis model against translation-based steganography
description	Steganography is the art of hiding information in ways that prevent the detection of a secret message. In Translation-based Steganography (TBS), the secret messages are encoded in the “noise” made via translation of natural language text programmed. The adversarial technique to extract the secret message is called steganalysis, which can be categorized into two types; targeted vs. blind. While targeted steganalysis is designed to attack a specific embedding algorithm, blind steganalysis use features extracted or selection from the medium to detect any anomalies that indicate a possibility that a secret data has been embedded within the medium. However, accuracy of blind steganalysis algorithms highly depend on the features selected from the input data especially when attacking embedding techniques in TBS. This thesis explore the potential of using stylometry or linguistic style to improve the representation of characteristics among the word distribution in distinguishing the stego text from the cover text for TBS. This is because all translated in TBS text have an intrinsic structural styles that can be used to improve the performance of a blind steganalysis model. The proposed stylometry-based blind steganalysis model consists of two stages, which are stylometric feature selection and classification. The proposed stylometric features selected from a set of cover text are categorized into two group features; lexical and syntactic features before implemented into the model Support Vector Machine (SVM) as the classifier. The performance of the stylometry-based blind steganalysis model is then evaluated based on all false rate, missing rate and accuracy rate and compared against three other standard classifiers in steganalysis; Naive Bayes (NB), k-Nearest Neighbor (k-NN), and Decision Tree (J48). The results showed that the stylometric features are impactful to a blind steganalysis model by giving higher detection performance. Meanwhile, SVM is the best classifier for stego text detection with significantly low processing time performance
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Mohd Lokman, Syiham
author_facet	Mohd Lokman, Syiham
author_sort	Mohd Lokman, Syiham
title	A stylometry approach for blind linguistic steganalysis model against translation-based steganography
title_short	A stylometry approach for blind linguistic steganalysis model against translation-based steganography
title_full	A stylometry approach for blind linguistic steganalysis model against translation-based steganography
title_fullStr	A stylometry approach for blind linguistic steganalysis model against translation-based steganography
title_full_unstemmed	A stylometry approach for blind linguistic steganalysis model against translation-based steganography
title_sort	stylometry approach for blind linguistic steganalysis model against translation-based steganography
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2023
url	http://eprints.uthm.edu.my/10995/1/24p%20SYIHAM%20MOHD%20LOKMAN.pdf http://eprints.uthm.edu.my/10995/2/SYIHAM%20MOHD%20LOKMAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/10995/3/SYIHAM%20MOHD%20LOKMAN%20WATERMARK.pdf
_version_	1804890133162360832

A stylometry approach for blind linguistic steganalysis model against translation-based steganography

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