Метод виявлення цифрових водяних знаків у мультимедійному контенті

Abstract

This paper focuses on the development of a method for detecting digital watermarks in multimedia content using modern machine learning techniques. With the rapid growth of digital media and the increasing risk of unauthorized distribution and manipulation, reliable watermark detection has become essential for copyright protection and content authentication. The proposed approach is based on the analysis of visual and statistical features of multimedia data, enabling the identification of embedded watermarks even without access to the original content. Particular attention is given to the use of deep learning models, such as convolutional neural networks, which provide high accuracy and robustness against various types of distortions and attacks. The advantages of the method, including adaptability and effectiveness in real-world conditions, are discussed along with challenges related to computational complexity and data requirements. The results demonstrate that deep learning-based approaches significantly improve the performance of digital watermark detection systems