A Multi-Layer Arabic Text Steganographic Method Based on Letter Shaping

Al Azzawi A.F

doi:10.5121/ijnsa.2019.11103

Abstract

Text documents are widely used, however, the text steganography is more difficult than other media because of a little redundant information. This paper presents a text steganography methodology appropriate for Arabic Unicode texts that do not use a normal sequential inserting process to overcome the security issues of the current approaches that are sensitive to steg-analysis. The Arabic Unicode text is kept within main unshaped letters, and the proposed method is used text file as cover text to hide a bit in each letter by reshaping the letters according to its position (beginning, middle, end of the word, or standalone), this hiding process is accomplished through multi-embedding layer where each layer contains all words with the same Tag detected using the POS tagger, and the embedding layers are selected randomly using the stego key to improve the security issues. The experimental result shows that the purposed method satisfied the hiding capacity requirements, improve security, and imperceptibility is better than currently developed approaches

Highlights

The image is the most well-liked carrier media for steganography due to its abundance out there on the web
This section gives a review of the fundamental concepts to achieve our goal and to implement an Arabic text steganography method considering utilizing from a Part Of Speech (Stanford-pos tagger-full-2018) [21], replacing the original Unicode letter with corresponding a suitable Unicode that keeps the letters with the same shape, a natural Language processing Toolkit (NLTK), and Python programming language are used as a development environment to satisfy the most common criteria in an efficient design for developing a text steganography algorithm
Kashid and space method utilizes from Arabic Kashida extension characters and the little space characters where Kashida character or space character is a combination of two approaches and used to insert a character into the cover text to hide either 1 bit or 3 bits which increases the cover size unacceptably affecting its quality, while the proposed method may hide a bit in each letter without inserting any character and its capacity will be increased rapidly if it combined with other approaches

Summary

Introduction

The image is the most well-liked carrier media for steganography due to its abundance out there on the web. This section gives a review of the fundamental concepts to achieve our goal and to implement an Arabic text steganography method considering utilizing from a Part Of Speech (Stanford-pos tagger-full-2018) [21], replacing the original Unicode letter with corresponding a suitable Unicode that keeps the letters with the same shape, a natural Language processing Toolkit (NLTK), and Python programming language are used as a development environment to satisfy the most common criteria in an efficient design for developing a text steganography algorithm. To achieve out our goal, Natural Language Processing Toolkit (NLTK), and Stanford-pos tagger(full-2018) are used to implement the proposed method. NLTK is used to split Arabic text file to a sequence of words, and Stanford-pos tagger is used to classify the cover text words according to its part of speech. Stanford-pos tagger(full-2018) is used to detect POS for the Arabic words found in the cover text and to construct multi-embedding layers

Objectives

Methods

Results

Conclusion