A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet  

作　　者：Fahd N.Al-Wesabi 

机构地区：[1]Department of Computer Science,King Khalid University,Muhayel Aseer,Saudi Arabia [2]Faculty of Computer and IT,Sana’a University,Sana’a,Yemen

出　　处：《Computers, Materials & Continua》2021年第1期195-211,共17页计算机、材料和连续体（英文）

基　　金：the Deanship of Scientific Research at King Khalid University for funding this work under grant number(R.G.P.2/55/40/2019),Received by Fahd N.Al-Wesabi.www.kku.edu.sa。

摘　　要：In this paper,a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents.The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach(SAMMZWA).Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach.The SAMMZWA approach embeds and detects the watermark logically without altering the original text document.The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques.To detect eventual tampering,SAMMZWA has been implemented and validated with attacked Arabic text.Experiments were performed on four datasets of varying lengths under multiple random locations of insertion,reorder and deletion attacks.The experimental results show that our method is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.

关 键 词：HMM NLP text analysis ZERO-WATERMARKING tampering detection 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]