Enhancing Video Protection: A Reversible Digital Watermarking approach using Swin features and Arnold Transform enabled Multi-Aggregation Model
Mali Satish Dilip, Agilandeeswari Loganathan · 2024
Nowadays, the widespread internet technology brings out rapid advancement in the use of videos for sharing huge amounts of secret data. Conversely, the privacy of transmitted digital content is jeopardized by digital image processing techniques that are capable of producing flawless image or video duplication. Moreover, providing security to digital records in the form of videos is a highly challenging task, which requires a fusion-based watermarking technique to protect the data from illegitimate access and fraudulent usage. In this investigation, a tiny Swin and Arnold Transform-enabled Multi-aggregation model was introduced to protect video based on digital watermarking characteristics at a very low computational cost. Here, the Swin-T features are extracted from the input video, over which the Arnold transform and multi-aggregation model is developed in two phases. The best embedding location is identified by using multi aggregation model initially at the embedding phase and the inverse Arnold transform for secret image (VIT Logo) embedding in a binary embedding location to obtain the embedded video. The secret image is extracted from the attacked embedded video using the Arnold transform-multi-aggregation model in the extraction phase. The developed data-hiding technique is also evaluated to compute the robustness using the evaluation parameters. The simulation results reveal that the developed scheme achieved Peak-Signal-to-Noise Ratio (PSNR) and Similarity Index Measure (SSIM) values of $64.57 \mathrm{~dB}$ and 0.9993 respectively.