Abstract:

Forensic infrastructures need to exchange data between others and are unable to operate independently without sharing information. Image forensic techniques play a crucial part in providing solutions to these challenges. This presents a comprehensive review of watermarking methods based on deep learning provided that no changes to the information are permitted during the transfer process. The study aims to present the operation of each, analyze the performance of the techniques and provide comparative evaluations including advantages and limitations. The results show the performance metrics include robustness, the quality of the resulting images, and overall capacity. The research highlights that algorithms improve the performance and achieve the security requirements of content authenticity for legal proceedings and public comment that maintaining public trust.