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 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.