Comparison of Eight Proposed Security Methods using Linguistic Steganography Text

The most common digital media exchanged via the Internet is in text form. The Arabic language is considered one of the most sensitive languages of content modification due to the presence of diacritics that can cause a change in the meaning. In this paper, an intelligent scheme is proposed for improving the reliability and security of the text exchanged via the Internet. The core mechanism of the proposed scheme depends on integrating the hidden Markov model and zero text watermarking techniques. The watermark key will be generated by utilizing the extracted features of the text analysis process using the third order and word level of the Markov model. The Embedding and detection processes of the proposed scheme will be performed logically without the effect of the original text. The proposed scheme is implemented using PHP with VS code IDE. The simulation results, using varying sizes of standard datasets, show that the proposed scheme can obtain high reliability and provide better accuracy of the common illegal tampering attacks. Comparison results with other baseline techniques show the added value of the proposed scheme.

Section: Related Workmentioning

confidence: 99%

Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

Duhayyim¹,

Alohali²,

Al‐Wesabi³

et al. 2022

“…The approach provides security against popular text attacks with a watermark distortion rate if, for all known attacks, it is greater than one. For the defense of English text by copyright, based on the present rate of ASCII non-vowel letters and terms, the conventional watermark approach [30] has been suggested.…”

Section: Related Workmentioning

confidence: 99%

An Optimal Text Watermarking Method for Sensitive Detecting of Illegal Tampering Attacks

Hilal¹,

Al‐Wesabi²,

Alamgeer³

et al. 2022

Due to the rapid increase in the exchange of text information via internet networks, the security and authenticity of digital content have become a major research issue. The main challenges faced by researchers are how to hide the information within the text to use it later for authentication and attacks tampering detection without effects on the meaning and size of the given digital text. In this paper, an efficient text-based watermarking method has been proposed for detecting the illegal tampering attacks on the Arabic text transmitted online via an Internet network. Towards this purpose, the accuracy of tampering detection and watermark robustness has been improved of the proposed method as compared with the existing approaches. In the proposed method, both embedding and extracting of the watermark are logically implemented, which causes no change in the digital text. This is achieved by using the third level and alphanumeric strategy of the Markov model as a text analysis technique for analyzing the Arabic contents to obtain its features which are considered as the digital watermark. This digital watermark will be used later to detecting any tampering of illegal attack on the received Arabic text. An extensive set of experiments using four data sets of varying lengths proves the effectiveness of our approach in terms of detection accuracy, robustness, and effectiveness under multiple random locations of the common tampering attacks.

“…As a comparison of tampering based on attack types, the results show that the most sensitive tampering detection in all attack volume scenarios is the insertion attack. The accuracy of tampering detection is carefully analysed and compared between HFDATAI and baseline algorithms ZWAFWMM [5] and RACAAT [30].…”

Section: Hfdatai Simulation and Experiments Findingsmentioning

confidence: 99%

Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack

Al‐Wesabi¹,

Iskandar²,

Alzahrani³

et al. 2021

In this article, a high-sensitive approach for detecting tampering attacks on transmitted Arabic-text over the Internet (HFDATAI) is proposed by integrating digital watermarking and hidden Markov model as a strategy for soft computing. The HFDATAI solution technically integrates and senses the watermark without modifying the original text. The alphanumeric mechanism order in the first stage focused on the Markov model key secret is incorporated into an automated, null-watermarking approach to enhance the proposed approach's efficiency, accuracy, and intensity. The first-level order and alphanumeric Markov model technique have been used as a strategy for soft computing to analyze the text of the Arabic language. In addition, the features of the interrelationship among text contexts and characteristics of watermark information extraction that is used later validated for detecting any tampering of the Arabic-text attacked. The HFDATAI strategy was introduced based on PHP with included IDE of VS code. Experiments of four separate duration datasets in random sites illustrate the fragility, efficacy, and applicability of HFDATAI by using the three common tampering attacks i.e., insertion, reorder, and deletion. The HFDATAI was found to be effective, applicable, and very sensitive for detecting any possible tampering on Arabic text.