Open Access
ARTICLE
Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack
1 Department of Computer Science, King Khalid University, Muhayel Aseer, Kingdom of Saudi Arabia
2 Faculty of Computer and IT, Sana’a University, Sana’a, Yemen
3 School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Malaysia
4 Department of Information Systems, King Khalid University, Muhayel Aseer, Kingdom of Saudi Arabia
5 Department of Computer Science, Faculty of Science & Arts of Baljurshi, Al-Baha University, KSA
* Corresponding Author: Fahd N. Al-Wesabi. Email:
Computers, Materials & Continua 2021, 68(3), 3789-3806. https://doi.org/10.32604/cmc.2021.017674
Received 06 February 2021; Accepted 15 March 2021; Issue published 06 May 2021
Abstract
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.Keywords
Cite This Article
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.