Transformations for linguistic steganography
type: CreativeWork
description: Linguistic steganography is a form of covert communication using natural language to conceal the existence of the hidden message. It is usually achieved by systematically making changes to a cover text, such that the manipulations, namely the very act of communication, are undetectable to an outside observer (human or computer). In this thesis, we explore three possible linguistic transformations — lexical substitution, adjective deletion and word ordering — which are able to generate alternatives for a cover text. For each transformation, we propose different transformation checkers in order to certify the naturalness of a modified sentence. Our lexical substitution checkers are based on contextual n-gram counts and the αskew divergence of those counts derived from the Google n-gram corpus. For adjective deletion, we propose an n-gram count method similar to the substitution n-gram checker and a support vector machine classifier using n-gram counts and other measures to classify deletable and undeletable adjectives in context. As for word ordering, we train a maximum entropy classifier using some syntactic features to determine the naturalness of a sentence permutation. The proposed transformation checkers were evaluated by human judged data, and the evaluation results are presented using precision and recall curves. The precision and recall of a transformation checker can be interpreted as the security level and the embedding capacity of the stegosystem, respectively. The results show that the proposed transformation checkers can provide a confident security level and reasonable embedding capacity for the steganography application. In addition to the transformation checkers, we demonstrate possible data encoding methods for each of the linguistic transformations. For lexical substitution, we propose a novel encoding method based on vertex colouring. For adjective deletion, we not only illustrate its usage in the steganography application, but also show that the ad…
abstract: Linguistic steganography is a form of covert communication using natural language to conceal the existence of the hidden message. It is usually achieved by systematically making changes to a cover text, such that the manipulations, namely the very act of communication, are undetectable to an outside observer (human or computer). In this thesis, we explore three possible linguistic transformations — lexical substitution, adjective deletion and word ordering — which are able to generate alternatives for a cover text. For each transformation, we propose different transformation checkers in order to certify the naturalness of a modified sentence. Our lexical substitution checkers are based on contextual n-gram counts and the αskew divergence of those counts derived from the Google n-gram corpus. For adjective deletion, we propose an n-gram count method similar to the substitution n-gram checker and a support vector machine classifier using n-gram counts and other measures to classify deletable and undeletable adjectives in context. As for word ordering, we train a maximum entropy classifier using some syntactic features to determine the naturalness of a sentence permutation. The proposed transformation checkers were evaluated by human judged data, and the evaluation results are presented using precision and recall curves. The precision and recall of a transformation checker can be interpreted as the security level and the embedding capacity of the stegosystem, respectively. The results show that the proposed transformation checkers can provide a confident security level and reasonable embedding capacity for the steganography application. In addition to the transformation checkers, we demonstrate possible data encoding methods for each of the linguistic transformations. For lexical substitution, we propose a novel encoding method based on vertex colouring. For adjective deletion, we not only illustrate its usage in the steganography application, but also show that the ad…
author: Chang, Ching-Yun
language: eng
keywords: Linguistic steganography
license: https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/4171717f-e482-4506-9e95-edc770a54c7f/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2013-07-01
date modified: 2026-07-22T22:24:31Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.100223