Design of an Efficient Multimodal Image Steganography Framework with Multi-Domain Feature Analysis and Secret Sharing Operations
Keywords:
Multimodal steganography, Visual cryptography, Shamir Secret Sharing, Multi-domain feature analysis, Data securityAbstract
The study introduces an innovative multimodal picture steganography framework addressing data security concerns in digital communication. The framework integrates multi-domain feature analysis and secret-sharing techniques for enhanced security confidentiality. Utilizing resizing and bitwise operations for steganography, along with (n, k) Shamir Secret Sharing for visual cryptography, the model excels in security measures. The algorithmic approaches of the proposed model designed for text, image, audio, and video processing within the multimedia landscape are thoroughly discussed. Comparative analyses demonstrate the superior performance of the proposed model in terms of RMSE, MAE and PSNR across audio, video, picture, and text modalities when compared to existing models. Significant improvements are observed in RMSE values, with reductions of 45%, 36%, and 15%, along with the improved PSNR values in the audio case compared to Chen L, Chen Y and Mo X, respectively. In the image case, the model consistently achieves lower RMSE and MAE values with higher PSNR values, showing improvements of about 48%, 35%, and 13% compared to Chen L, Chen Y and Mo X. Video steganography sees approximately 30% and 21% reductions in RMSE values compared to Chen L and Chen Y, with improved PSNR values. Text steganography displays noteworthy advancements compared to Chen L, including a 13% reduction in delay compared to Mo X. The proposed model outperforms existing models Chen L, Chen Y and Mo X in audio, video, image, and text steganography. The proposed model demonstrates superior performance and reduced processing time and provides an effective solution for securely embedding information. With applications spanning digital media, telecommunications, and information security, it offers a reliable and versatile solution for secure data embedding in diverse scenarios.
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