Heuristic Optimization Algorithm Based Watermarking on Content Authentication and Tampering Detection for English Text

Text information is a natural language dependent, which enhances reliability and security of text data exchanged through Internet networks and is becoming main concern for researchers. Content authentication, Tampering detection, and integrity verification of digital content are considered challenges in the information and communication exchange area through the Internet. Watermarking algorithms emerge as a potential method for achieving this with text. In simple words, text watermarking is embedding imperceptible text messages within the content that serve as unique signatures or identifiers. The text message has data regarding the content creator, copyright data, or other metadata utilized for authentication purposes. Therefore, this study presents a new Coyote Optimization Algorithm with Watermarking-based Content Authentication and Tampering Detection (COAW-CATD) technique for English text. The presented COAW-CATD technique aims to secure the English text via content authentication and tampering recognition. To accomplish this, the presented COAW-CATD technique designs a zero-watermarking (ZWM) approach to produce watermarks depending on the textual content. The generated watermark can be extracted to assure the authentication of the text document. Moreover, the COA can be utilized to optimize the placement of the watermarks in the content to ensure that it is imperceptible and robust to tampering. The experimental outcomes of the COAW-CATD algorithm are tested utilizing a series of simulations and the comparative study reported its superior performance with improved tampering detection accuracy of 95.93%.