# A Comparative Analysis of Arabic Text Steganography
## 3 Text Steganography
### Format-Based Steganography
#### 3.3.1 English-Based  
The modification of a written status of the mark-up letter to hide the secret message was introduced by the authors of [51]. This was exploited to analyze the concealed secret information in hypertext. Mark-up letters determine the secret bits used to reveal the length of hidden messages. Machine translation was employed by the authors of [52] to hide a secret data. This embedded method translates the transmitted text and allows the source to be kept in its original form. A code representation method known as secret steganography code was proposed [53], which employs the positions of vowels and consonants according to the grammatical sequence.  
The authors of [54] used right-to-left and left-to-right remark to conceal information. This embedded method hides the secret data/message without changing the file's information. It also avoids the retyping problem by converting the file into PDF format. Encryption with Cover text and Reordering (ECR) was proposed [55], which uses XOR operation. It merges two characters when enciphered in the original message. Because the suggested mechanism considers encryption and reordering processes, it is convenient to implement cloud computing.  
The algorithm described by the authors of [40] utilizes several invisible character symbols for covering 4 bits between alphabets in word symbols such as left remark, right remark, and zero-width joiner. The algorithm can only be applied to specific languages, hence there is a need to extend its embedded method to be applied in any language. The concept of utilizing the font attributes and character frequency to embed the secret characters was presented by the authors of [56]. To accomplish the uniform appropriation in stego characters with the uniform hiding likelihood, this method integrates four models:  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Secret Message** & **Cover Text** & **Stego Text** \\ \hline \multirow{2}{*}{110} & “All birds can fly. This is a & “All birds can fly. This is a \\  & bird. Ostrich can also fly.” & bird. Ostrich can also fly.” \\ \hline \hline \end{tabular}
\end{table}
Table 4: Example of format-based text steganography (Data from [37]).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Category** & **Description** \\ \hline Random and Statistical Generation & This method is not based on a specific text. However, the generated text is meaningless and raise suspicions. The computational time is also increased. \\  & The invisibility is improved, but the method still suffers from low capacity. Also, searching through a dictionary \\ Linguistic steganography & for a suitable word/letter to match the secret word/letter \\  & increases the computational time. \\ Format-based & This method improves invisibility and computational time. \\  & Nevertheless, it suffers from low embedding capacity. \\ \hline \hline \end{tabular}
\end{table}
Table 5: The main differences between the 3 categories.  
Frequency Normalization Set (FNS), Character String Mapping (CSM), embedding, and extracting.  
Text justification was considered by the authors of [7] by justifying the cover text's host line based on the character's frequency in the confidential message. This method was deployed in both electronic and printed details. In the same line, the concealed method introduced by the authors of [57] changes the length per line in the text document to embed the secret bits, which are covered using white space between words and an extended line in the cover text.