ech T Press Science Computers, Materials & Continua DOI:10.32604/cmc.2021.017674 Article Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack Fahd N. Al-Wesabi 1,2, * , Huda G. Iskandar 2,3 , Saleh Alzahrani 4 , Abdelzahir Abdelmaboud 4 , Mohammed Abdul 4 , Nadhem Nemri 4 , Mohammad Medani 4 and Mohammed Y. Alghamdi 5 1 Department of Computer Science, King Khalid University, Muhayel Aseer, Kingdom of Saudi Arabia 2 Facultyof 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: fwesabi@gmail.com Received: 06 February 2021; Accepted: 15 March 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 strat- egy for soft computing. The HFDATAI solution technically integrates and senses the watermark without modifying the original text. The alphanumeric mechanism order in the frst stage focused on the Markov model key secret is incorporated into an automated, null-watermarking approach to enhance the proposed approach’s effciency, accuracy, and intensity. The frst-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 intro- duced based on PHP with included IDE of VS code. Experiments of four separate duration datasets in random sites illustrate the fragility, effcacy, and applicability of HFDATAI by using the three common tampering attacks i.e., insertion, reorder, and deletion. The HFDATAI was found to be effec- tive, applicable, and very sensitive for detecting any possible tampering on Arabic text. Keywords: Watermarking; soft computing; text analysis; hidden Markov model; content authentication 1 Introduction For the research community, the reliability and security of exchanged text data through the internet is the most promising and challenging feld. In communication technologies, authentica- tion of content and automated text verifcation of honesty in different Languages and formats are of great signifcance. Numerous applications for instance; e-Banking and e-commerce render 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.