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A Robust Cross-Channel Image Watermarking technique for Tamper Detection and its Precise Localization
Author(s) -
Muhammad Ashraf,
Adnan Nadeem,
Oussama Benrhouma,
Muhammad Sarim,
Kashif Rizwan,
Amir Mehmood
Publication year - 2025
Publication title -
ieee open journal of the computer society
Language(s) - English
Resource type - Magazines
eISSN - 2644-1268
DOI - 10.1109/ojcs.2025.3589948
Subject(s) - computing and processing
Several watermarking techniques have been suggested to safeguard the integrity of transmitted images in public video surveillance applications. However, these techniques have a critical drawback in their embedding schemes: the watermark is limited to residing in a narrow traceable space to avoid fidelity issues. Such a protection layer can be evaluated or forcefully removed to breach data security. Once the protection layer (watermark) is removed, a watermarking algorithm cannot pinpoint the falsified regions in affected images and gives a binary answer. Consequently, attackers can present the falsification of visual elements as a non-malicious perturbation. Such a type of attack poses a serious security challenge. This study introduces a novel cross-channel image watermarking technique that randomly scatters the watermark pattern across a 24-bit image structure so that no emergence of embedding signatures and fidelity issues occurs after the process. Chaotic systems are employed to leverage their sensitivity to initial conditions and control parameters, resulting in high confusion and diffusion properties in the proposed scheme. The protection layer is completely intractable as it is randomly scattered in the entire RGB space, making it very hard to remove without leaving a clear footprint in affected images. This method creates a good balance between security and imperceptibility, it effectively detects and localizes falsified regions in tampered images, and maintains this ability until clear evidence of a removal attempt emerges in histograms. This property makes proposed algorithm a preferred choice for data integrity protection; it achieved an average F1-score of 0.97 for tamper detection.

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