4KSecure: A Universal Method for Active Manipulation Detection in Images of Any Resolution

This paper presents a method for actively safeguarding image integrity based on embedding a hidden signature generated by a neural network. The proposed solution utilizes two cooperating networks: the first one is responsible for generating a signature pattern that is difficult to detect, while the second one embeds this signature into the original image in a way that ensures high visual transparency. This automatically generated signature enables the detection of manipulations in the image and allows for localizing areas where integrity violations have occurred. The main innovation of the proposed approach lies in its ability to handle images of virtually any resolution, including widely used standards in modern communication and publications, such as HD (1280 × 720), Full HD (1920 × 1080) and even 4K (3840 × 2160). This represents a significant improvement over most existing methods, which are typically limited to the small, square images (e.g., 256 × 256 or 512 × 512 pixels) commonly found in popular object classification datasets, such as ImageNet (approximately 224 × 224 pixels). As a result, the proposed method opens new possibilities for actively securing the integrity of large and non-standard image formats while maintaining reasonable computational requirements. It surpasses previous limitations in terms of scalability and image proportions.