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Proposing a High-Robust Approach for Detecting the Tampering Attacks on English Text Transmitted via Internet

机译:提出一种用于检测通过Internet传输的英语文本的篡改攻击的高强度方法

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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 during detection process to detect any tampering. INLPETWA approach has been implemented by self-developed program using PHP with VS code IDE. INLPETWA approach has been proved with various experiments and simulation scenarios. Comparison results with baseline approaches also show that the proposed approach is appropriate to detect all types of tampering attacks. The paper includes implications for integrating natural language processing and text-watermarking to propose an intelligent solution. This paper fulfils an identified need to study how we can use a robust text information via various Internet applications.
机译:在本文中,提出了一种强大的方法(智能自然语言处理和英语文本水印方法),以通过将零文本水印和隐藏的Markov模型集成为软计算和自然语言处理技术来篡改英语文本的检测。在Inlpetwa方法中,嵌入和检测在逻辑上进行的水印键,而不会改变纯文本。隐藏马克罗夫模型的第二克和单词机制用作自然文本分析技术,以提取英文文本特征,并将其用作水印键,并在逻辑上嵌入它们并在检测过程中验证它们以检测任何篡改。使用VS Code IDE使用PHP,通过自主研发的程序实现了Inlpetwa方法。 inlpetwa方法已经证明了各种实验和仿真方案。与基线方法的比较结果还表明,所提出的方法适合检测所有类型的篡改攻击。本文包括对整合自然语言处理和文本水印的影响,提出智能解决方案。本文符合所识别的需要研究我们如何通过各种Internet应用程序使用强大的文本信息。

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