Open Access

ARTICLE

Securing Arabic Contents Algorithm for Smart Detecting of Illegal Tampering Attacks

Mesfer Al Duhayyim¹, Manal Abdullah Alohali², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal^5,*, Mohammad Medani³, Manar Ahmed Hamza⁵
1 Department of Natural and Applied Sciences, College of Community - Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia
2 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Saudi Arabia
3 Department of Computer Science, King Khalid University, Muhayel Aseer, Saudi Arabia
4 Faculty of Computer and IT, Sana’a University, Sana’a, Yemen
5 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia
* Corresponding Author: Anwer Mustafa Hilal. Email:

Computers, Materials & Continua 2022, 70(2), 2879-2894. https://doi.org/10.32604/cmc.2022.019594

Received 19 April 2021; Accepted 19 June 2021; Issue published 27 September 2021

Abstract

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.

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Keywords

Tampering detection; zero-watermarking; soft computing; text analysis; hidden Markov model

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