Abstract
Text information depends primarily on natural languages processing. Improving the security and usability of text information shared through the public internet has therefore been the most demanding problem facing researchers. In contact and knowledge sharing through the Internet, the authentication of content and the identification of digital content are becoming a key problem. Therefore, in this paper, a fragile approach of zero-watermarking based on natural language processing has been developed for authentication of content and prevention of misuse of Arabic texts distributed over the Internet. According to the proposed approach, watermark embedding, and identification was technically carried out such that the initial text document did not need to be changed to embed a watermark. The automated zero-watermarking approaches have been combined with a second-tier word order framework based on the Markov model to boost the efficiency, precision, ability, and fragility of the existing researches. This second-tier of the Markov-model has been used as a natural language processing technique to analyze Arabic-text and extract the features of the interrelationship between textual contexts. Moreover, the extracted features have been utilized as information of watermark and then validated to identify any possible tampering with the attacked Arabic-text. The recommended solution has been applied with VS code IDE using PHP. The experimental results using four datasets of varying size show that the proposed approach can obtain better detection accuracy of tampering attacks, effectiveness and high fragility for common random insertion, reorder and deletion attacks for common attacks, e.g., Comparison results with baseline approaches also show the advantages of the proposed approach.