Anwer Mustafa Hilal^1,*, Fahd N. Al-Wesabi^2,3, 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 - 11 October 2021

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… More >

Fahd N. Al-Wesabi^1,*, Huda G. Iskandar², Mohammad Alamgeer³, Mokhtar M. Ghilan²

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1267-1283, 2020, DOI:10.32604/iasc.2020.013782 - 24 December 2020

Abstract In this paper, a robust approach INLPETWA (an Intelligent Natural Language Processing and English Text Watermarking Approach) is proposed to tampering detection of English text by integrating zero text watermarking and hidden Markov model as a soft computing and natural language processing techniques. In the INLPETWA approach, embedding and detecting the watermark key logically conducted without altering the plain text. Second-gram and word mechanism of hidden Markov model is used as a natural text analysis technique to extracts English text features and use them as a watermark key and embed them logically and validates them More >