scholarly journals A review of arabic text steganography: past and present

2020 ◽  
Vol 17 (2) ◽  
pp. 1040
Author(s):  
Suhaibah Jusoh ◽  
Aida Mustapha ◽  
Azizan Ismail ◽  
Roshidi Din
Keyword(s):  
Comparative Analysis ◽  
English Language ◽  
Arabic Language ◽  
Secret Message ◽  
Arabic Text ◽  
Hidden Information ◽  
Secret Information ◽  
Text Steganography

<span>Steganography is a strategy for hiding secret information in a cover document in order to avoid attacker from predict about hidden information. Steganography exploit cover message, for instance text, audio, picture and video to hide the secret message. Before this, linguistic text steganographic techniques are implemented just for the English language. But nowadays different languages are used to hide the data like Arabic language. This language is still new in the steganography and still need practices for empowerment. This paper will present the text steganographic method for Arabic language, scholar paper within 5 year will be analyze and compared. The main objective of this paper is to give the comparative analysis in the Arabic steganography method that has been applied by previous researchers. Finally, the disadvantage and advantage of the method also will be presented in this paper.</span>

scholarly journals A Comparative Analysis of Arabic Text Steganography

2021 ◽  
Vol 11 (15) ◽  
pp. 6851
Author(s):  
Reema Thabit ◽  
Nur Izura Udzir ◽  
Sharifah Md Yasin ◽  
Aziah Asmawi ◽  
Nuur Alifah Roslan ◽  
...  
Keyword(s):  
Evaluation Criteria ◽  
Arabic Language ◽  
Text Messages ◽  
Secret Message ◽  
Sensitive Information ◽  
Arabic Text ◽  
Ideal Object ◽  
Internet Users ◽  
Text Steganography ◽  
Text Content

Protecting sensitive information transmitted via public channels is a significant issue faced by governments, militaries, organizations, and individuals. Steganography protects the secret information by concealing it in a transferred object such as video, audio, image, text, network, or DNA. As text uses low bandwidth, it is commonly used by Internet users in their daily activities, resulting a vast amount of text messages sent daily as social media posts and documents. Accordingly, text is the ideal object to be used in steganography, since hiding a secret message in a text makes it difficult for the attacker to detect the hidden message among the massive text content on the Internet. Language’s characteristics are utilized in text steganography. Despite the richness of the Arabic language in linguistic characteristics, only a few studies have been conducted in Arabic text steganography. To draw further attention to Arabic text steganography prospects, this paper reviews the classifications of these methods from its inception. For analysis, this paper presents a comprehensive study based on the key evaluation criteria (i.e., capacity, invisibility, robustness, and security). It opens new areas for further research based on the trends in this field.

scholarly journals Traid-bit embedding process on Arabic text steganography method

2021 ◽  
Vol 10 (1) ◽  
pp. 493-500
Author(s):  
Roshidi Din ◽  
Reema Ahmed Thabit ◽  
Nur Izura Udzir ◽  
Sunariya Utama
Keyword(s):  
Intellectual Property ◽  
Continuous Improvement ◽  
High Capacity ◽  
Arabic Language ◽  
The Internet ◽  
Arabic Text ◽  
Art And Science ◽  
Text Steganography ◽  
Sharp Edges ◽  
Audio Video

The enormous development in the utilization of the Internet has driven by a continuous improvement in the region of security. The enhancement of the security embedded techniques is applied to save the intellectual property. There are numerous types of security mechanisms. Steganography is the art and science of concealing secret information inside a cover media such as image, audio, video and text, without drawing any suspicion to the eavesdropper. The text is ideal for steganography due to its ubiquity. There are many steganography embedded techniques used Arabic language to embed the hidden message in the cover text. Kashida, Shifting Point and Sharp-edges are the three Arabic steganography embedded techniques with high capacity. However, these three techniques have lack of performance to embed the hidden message into the cover text. This paper present about traid-bit method by integrating these three Arabic text steganography embedded techniques. It is an effective way to evaluate many embedded techniques at the same time, and introduced one solution for various cases.

scholarly journals New text steganography method using the arabic letters dots

2021 ◽  
Vol 21 (3) ◽  
pp. 1784
Author(s):  
Ahlam R. Khekan ◽  
Hiba Mohammed Wajeh Majeed ◽  
Omer F. Ahmed Adeeb
Keyword(s):  
Storage Capacity ◽  
New Technology ◽  
Arabic Language ◽  
Secret Message ◽  
New Methods ◽  
Arabic Characters ◽  
Proposed Model ◽  
Text Steganography ◽  
Hide Data ◽  
Development Methods

<span>With the increasing technological and electronic development, methods have been developed to hide important information using text steganography as a new technology, since it is not noticeable and easy to send and receive. The use of the Arabic language is one of the new methods used to hide data. In this work, we preview our method that depends to use the part of Arabic language properties to embed the secret English message in to cover text to create text steganography. More than half of the Arabic characters contain dots. Several characters have upper dots and others have lower dots. Some have one dot others have two dots. Few have even three dots. In this new idea, we will use the dots of charters to embed the English secret message. First, we will compress the secret message by using the 5-Bit Encoding (T-5BE) to make the cover text able to embed more bits of the secret message by 37.5%. Then we start using the Arabic semantic dictionary to correct the hiding path and enhancement the stego-cover text to eliminate errors caused by switching words. In this research, we were able to extract experimental results that show that the proposed model achieves high masking accuracy in addition to the storage capacity of the cover text.</span>

scholarly journals A Novel Approach for Arabic Text Steganography Based on the “BloodGroup” Text Hiding Method

2017 ◽  
Vol 7 (2) ◽  
pp. 1482-1485
Author(s):  
S. Malalla ◽  
F. R. Shareef
Keyword(s):  
Blood Group ◽  
Time Complexity ◽  
Third Party ◽  
Secret Message ◽  
Covert Communication ◽  
Arabic Text ◽  
Hiding Capacity ◽  
Novel Approach ◽  
Text Steganography

Steganography is the science of hiding certain messages (data) in groups of irrelevant data possibly of other form. The purpose of steganography is covert communication to hide the existence of a message from an intermediary. Text Steganography is the process of embedding secret message (text) in another text (cover text) so that the existence of secret message cannot be detected by a third party. This paper presents a novel approach for text steganography using the Blood Group (BG) method based on the behavior of blood group. Experimentally it is found that the proposed method got good results in capacity, hiding capacity, time complexity, robustness, visibility, and similarity which shows its superiority as compared to most several existing methods.

scholarly journals Integrating Light-Weight Cryptography with Diacritics Arabic Text Steganography Improved for Practical Security Applications

2020 ◽  
Vol 3 (1) ◽  
pp. 13-30
Author(s):  
Malak G. Alkhudaydi ◽  
Adnan A. Gutub
Keyword(s):  
Data Security ◽  
Arabic Language ◽  
Arabic Text ◽  
Light Weight ◽  
Authentic Texts ◽  
Security Applications ◽  
Text Steganography ◽  
Holy Quran ◽  
The Holy Quran ◽  
To Come

Cryptography and steganography are combined to provide practical data security. This paper proposes integrating light-weight cryptography with improved Arabic text steganography for optimizing security applications. It uses light-weight cryptography to cope with current limited device capabilities, to provide acceptable required security. The work tests hiding encrypted secret information within Arabic stego-cover texts, using all common diacritics found naturally in the Arabic language. The study considers different challenging situations and scenarios in order to evaluate security practicality. It further carries out simulations on some short texts from the Holy Quran, taking them as standard authentic texts, that are fixed and trusted, therefore providing realistic study feedback that is worth monitoring. Our improved approach features preferred capacity and security, surpassing the best previous diacritics stego approach, showing interesting potential results for attractive enlightening exploration to come.

scholarly journals Keyword Extraction from Arabic Text using the Page Rank Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 3495-3504
Keyword(s):  
English Language ◽  
Language Testing ◽  
Arabic Language ◽  
Extraction System ◽  
Keyword Extraction ◽  
Arabic Text ◽  
Keyphrase Extraction ◽  
Page Rank ◽  
Testing Dataset ◽  
F Measure

This paper describes how keywords are extracted from Arabic text using the page rank algorithm, by constructing a graph whose vertices are formed by candidate words that are extracted from the title and the abstract of a given Arabic text after applying a tagging filter to that text. Next, a co-occurrence relation is applied to draw the edges between the vertices within specified window sizes. Then, the page rank algorithm is applied to the graph to rank the importance of each keyword. Finally, the vertices are sorted in descending order by their page rank scores and the tokens with highest scores are chosen as the keywords. Several experiments were conducted on a dataset that consisted of 100 Arabic academic articles for training and 50 for testing. The results were evaluated by using precision, recall, and the F-measure. The maximum recall achieved on the dataset was 63%, as not all the manually identified keywords and keyphrases existed in the article abstracts and titles. The proposed method achieved 25% of recall, which is acceptable as it is comparable to that of a method in the literature that was applied to an English language testing dataset that consisted of 500 English documents, which achieved 42% of recall where the maximum recall percentage of the testing dataset was 78%. Despite the difficulties and challenges in searching for keywords in the Arabic language and using fewer documents in the Arabic testing dataset than in the English, it can be concluded that the proposed keyword and keyphrase extraction system using the page rank algorithm works well

Improving Arabic Text Classification Using P-Stemmer

2020 ◽  
Vol 13 ◽  
Author(s):  
Tarek Kanan ◽  
Bilal Hawashin ◽  
Shadi Alzubi ◽  
Eyad Almaita ◽  
Ahmad Alkhatib ◽  
...  
Keyword(s):  
Language Processing ◽  
Text Classification ◽  
Text Categorization ◽  
English Language ◽  
Arabic Language ◽  
Online News ◽  
Support Vector ◽  
Arabic Text ◽  
Fast Learning ◽  
Arabic Text Classification

Introduction: Stemming is an important preprocessing step in text classification, and could contribute in increasing text classification accuracy. Although many works proposed stemmers for English language, few stemmers were proposed for Arabic text. Arabic language has gained increasing attention in the previous decades and the need is vital to further improve Arabic text classification. Method: This work combined the use of the recently proposed P-Stemmer with various classifiers to find the optimal classifier for the P-stemmer in term of Arabic text classification. As part of this work, a synthesized dataset was collected. Result: The previous experiments show that the use of P-Stemmer has a positive effect on classification. The degree of improvement was classifier-dependent, which is reasonable as classifiers vary in their methodologies. Moreover, the experiments show that the best classifier with the P-Stemmer was NB. This is an interesting result as this classifier is wellknown for its fast learning and classification time. Discussion: First, the continuous improvement of the P-Stemmer by more optimization steps is necessary to further improve the Arabic text categorization. This can be made by combining more classifiers with the stemmer, by optimizing the other natural language processing steps, and by improving the set of stemming rules. Second, the lack of sufficient Arabic datasets, especially large ones, is still an issue. Conclusion: In this work, an improved P-Stemmer was proposed by combining its use with various classifiers. In order to evaluate its performance, and due to the lack of Arabic datasets, a novel Arabic dataset was synthesized from various online news pages. Next, the P-Stemmer was combined with Naïve Bayes, Random Forest, Support Vector Machines, KNearest Neighbor, and K-Star.

scholarly journals OCR with Tesseract, Amazon Textract, and Google Document AI: A Benchmarking Experiment

2021 ◽  
Author(s):  
Thomas Hegghammer
Keyword(s):  
Character Recognition ◽  
Optical Character Recognition ◽  
English Language ◽  
Computational Analysis ◽  
Arabic Language ◽  
Artificial Noise ◽  
Arabic Text ◽  
Optical Character ◽  
Different Types ◽  
Better Than

Optical Character Recognition (OCR) can open up understudied historical documents to computational analysis, but the accuracy of OCR software varies. This article reports a benchmarking experiment comparing the performance of Tesseract, Amazon Textract, and Google Document AI on images of English and Arabic text. English-language book scans (n=322) and Arabic-language article scans (n=100) were replicated 43 times with different types of artificial noise for a corpus of 18,568 documents, generating 51,304 process requests. Document AI delivered the best results, and the server-based processors (Textract and Document AI) were substantially more accurate than Tesseract, especially on noisy documents. Accuracy for English was considerably better than for Arabic. Specifying the relative performance of three leading OCR products and the differential effects of commonly found noise types can help scholars identify better OCR solutions for their research needs. The test materials have been preserved in the openly available "Noisy OCR Dataset" (NOD).

scholarly journals A Proposed Arabic Text Encryption Method Using Multiple Ciphers

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 04) ◽  
pp. 319-326
Author(s):  
Ammar Sabeeh Hmoud Altamimi ◽  
Ali Mohsin Kaittan
Keyword(s):  
Mathematical Model ◽  
English Language ◽  
Selection Process ◽  
Arabic Language ◽  
Arabic Text ◽  
Method Selection ◽  
Encryption Method ◽  
Better Than

Most encryption techniques are deals with English language, but that deals with Arabic language are few. Therefore, many researchers interests with encryption ciphers that applied on text which wrote in Arabic language. This reason is behind this paper. In this paper, there are three cipher methods implemented together on Arabic text. Using more than one cipher method is increase the security of algorithm used. Each letter of plaintext is encrypted by a specified cipher method. Selection process of one of three cipher methods used in this work is done by controlling process that selects one cipher method to encrypt one letter of plaintext. The cipher methods that used in this paper are RSA, Playfair and Vignere. Each one of them has different basis mathematical model. This proposed encryption Arabic text method gives results better than previous related papers.

scholarly journals FEATURES OF HIDING INFORMATION IN IMAGES WITH USING THE LEAST SIGNIFICANT BIT

2020 ◽  
Vol 20 ◽  
pp. 17-22
Author(s):  
A. Lagun ◽  
O. Polotai
Keyword(s):  
Secret Message ◽  
Pseudorandom Sequence ◽  
Text File ◽  
Least Significant Bit ◽  
Hidden Information ◽  
Digital Text ◽  
Secret Information ◽  
Text Information ◽  
Image Pixels ◽  
Sequence Generator

In the article has considered the peculiarities of steganographic algorithms implemenation for hiding information in inmoveable images. Authors has described different embedding algorithms which use the method of least significant bit. In particular, the use of digital filtering allows you to better select the necessary pixels for embedding, and the use of a pseudorandom sequence generator allows you to more effectively hide secret information, complicating the search for secret information to the attacker.From the existing color palettes to represent inmoveable images have been selected the most common RGB pal-ette, which contains red, green, and blue intensities to produce image pixels. Colors that are less sensitive to the human eye are used to form the filled steganographic containers to provide additional visual stability.Also, in the paper authors have investigated the features of hiding digital text information in a inmoveable image as a BMP file and have realized an algorithm that for images of different size allows you to hide a text file of the necessary size. In particular, the number of bytes of the secret message is written to the original container to retrieve the required number of characters during searching. In addition, it takes into account the peculiarities of forming a BMP file that contains additional alignment bytes of the string.In general, the algorithm allows you to select a container file of the appropriate size to hide the secret information, as well as the colors of the palette in which the information will be embedded. The extracting of secret information occurs until the number of bytes of the hidden message is reached. This value has recorded at the beginning of the hiding text. You can use encryption or compression algorithms to complication searching of clear text by attacker. Only users those who are aware of the algorithms used and perhaps the keys will be able to read the hidden information correctly.

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