期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
Arabic Feature-Based Text Watermarking Technique for Sensitive Detecting Tampering Attack 被引量:1
1
作者 Fahd N.Al-Wesabi Huda G.Iskandar +5 位作者 Saleh Alzahrani Abdelzahir Abdelmaboud mohammed Abdul Nadhem Nemri Mohammad Medani mohammed y.alghamdi 《Computers, Materials & Continua》 SCIE EI 2021年第9期3789-3806,共18页
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 ... 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 the Arabic language.In addition,the features of the interrelationship among text contexts and characteristics of watermark information extraction that is used later validated for detecting any tampering of the Arabic-text attacked.The HFDATAI strategy was introduced based on PHP with included IDE of VS code.Experiments of four separate duration datasets in random sites illustrate the fragility,efficacy,and applicability of HFDATAI by using the three common tampering attacks i.e.,insertion,reorder,and deletion.The HFDATAI was found to be effective,applicable,and very sensitive for detecting any possible tampering on Arabic text. 展开更多
关键词 WATERMARKING soft computing text analysis hidden Markov model content authentication
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部