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Search Results (6)
  • Open Access

    ARTICLE

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

    Anwer Mustafa Hilal1,*, Fahd N. Al-Wesabi2,3, Mohammed Alamgeer4, Manar Ahmed Hamza1, Mohammad Mahzari5, Murad A. Almekhlafi6

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5583-5600, 2022, DOI:10.32604/cmc.2022.019686

    Abstract 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… More >

  • Open Access

    ARTICLE

    An Optimized English Text Watermarking Method Based on Natural Language Processing Techniques

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1519-1536, 2021, DOI:10.32604/cmc.2021.018202

    Abstract In this paper, the text analysis-based approach RTADZWA (Reliable Text Analysis and Digital Zero-Watermarking Approach) has been proposed for transferring and receiving authentic English text via the internet. Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it. Text analysis and text zero-watermarking techniques have been integrated by… More >

  • Open Access

    ARTICLE

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

    Fahd N. Al-Wesabi1,2,*, Huda G. Iskandar2,3, Saleh Alzahrani4, Abdelzahir Abdelmaboud4, Mohammed Abdul4, Nadhem Nemri4, Mohammad Medani4, Mohammed Y. Alghamdi5

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3789-3806, 2021, DOI:10.32604/cmc.2021.017674

    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… More >

  • Open Access

    ARTICLE

    Tamper Detection and Localization for Quranic Text Watermarking Scheme Based on Hybrid Technique

    Ali A. R. Alkhafaji*, Nilam Nur Amir Sjarif, M. A. Shahidan, Nurulhuda Firdaus Mohd Azmi, Haslina Md Sarkan, Suriayati Chuprat

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 77-102, 2021, DOI:10.32604/cmc.2021.015770

    Abstract The text of the Quran is principally dependent on the Arabic language. Therefore, improving the security and reliability of the Quran’s text when it is exchanged via internet networks has become one of the most difficult challenges that researchers face today. Consequently, the diacritical marks in the Holy Quran which represent Arabic vowels () known as the kashida (or “extended letters”) must be protected from changes. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR), and Normalized Cross-Correlation (NCC); thus, the location for tamper… More >

  • Open Access

    ARTICLE

    A Reliable NLP Scheme for English Text Watermarking Based on Contents Interrelationship

    Fahd N. Al-Wesabi1,2,*, Saleh Alzahrani3, Fuad Alyarimi3, Mohammed Abdul3, Nadhem Nemri3, Mohammed M. Almazah4

    Computer Systems Science and Engineering, Vol.37, No.3, pp. 297-311, 2021, DOI:10.32604/csse.2021.015915

    Abstract In this paper, a combined approach CAZWNLP (a combined approach of zero-watermarking and natural language processing) has been developed for the tampering detection of English text exchanged through the Internet. The third gram of alphanumeric of the Markov model has been used with text-watermarking technologies to improve the performance and accuracy of tampering detection issues which are limited by the existing works reviewed in the literature of this study. The third-grade level of the Markov model has been used in this method as natural language processing technology to analyze an English text and extract the textual characteristics of the given… More >

  • Open Access

    ARTICLE

    Payload Capacity Scheme for Quran Text Watermarking Based on Vowels with Kashida

    Ali A.R. Alkhafaji1,*, Nilam Nur Amir Sjarif1, M.A Shahidan1, Nurulhuda Firdaus Mohd Azmi1, Haslina Md Sarkan1, Suriayati Chuprat1, Osamah Ibrahim Khalaf2, Ehab Nabiel Al-Khanak3

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3865-3885, 2021, DOI:10.32604/cmc.2021.015803

    Abstract The most sensitive Arabic text available online is the digital Holy Quran. This sacred Islamic religious book is recited by all Muslims worldwide including non-Arabs as part of their worship needs. Thus, it should be protected from any kind of tampering to keep its invaluable meaning intact. Different characteristics of Arabic letters like the vowels (), Kashida (extended letters), and other symbols in the Holy Quran must be secured from alterations. The cover text of the Quran and its watermarked text are different due to the low values of the Peak Signal to Noise Ratio (PSNR) and Embedding Ratio (ER).… More >

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