Fortifying Textual Integrity: Evolutionary Optimization-powered Watermarking for Tampering Attack Detection in Digital Documents

Abstract

Digital document helps as the lifeblood of present communication, yet their vulnerability to tampering poses major safety anxieties. Digital text watermarking is an effective mechanism to protect the reliability of text-based data in the digital. Introducing a hidden layer of accountability and safety, allows individuals and organizations to trust the written word and make sure the truth behind all the files. Watermarking model identifies the tampering attack by inspecting the embedded signature for distortions or alterations. Watermarks can able to mechanically classify and repair themselves once tampered with, improving document resilience. Watermarking acts as a powerful tool to detect tampering attacks in digital document. By embedding strong and imperceptible watermarks in document distribution or creation, alterations are recognized by specialized procedure. This study introduces an Evolutionary Optimizer-powered Watermarking for Tampering Attack Detection in Digital Document (EO-WTAD3) model. The main intention of EO-WTAD3 approach is to support textual integrity using the applications of metaheuristic optimizer algorithm based watermarking technique for detecting tampering attacks in digital document. In the EO-WTAD3 method, a digital watermarking method has been proposed for the ownership verification and document copyright protection using data mining concept. Moreover, the EO-WTAD3 technique utilizes the concepts of data mining to define appropriate characteristics from the document for embedding watermarks. Moreover, fractional gorilla troops optimization (FGTO) algorithm can be applied for the assortment of optimal situation of watermarks in the content, ensuring both imperceptibility and strong to tamper. The performance validation of the EO-WTAD3 methodology takes place employing multiple datasets. The extensive result analysis portrayed that the EO-WTAD3 system accomplishes improve solution with other existing approaches with respect distinct aspects.