Data Privacy Protection Using Lucas Series Based Hybrid Reversible Watermarking Approach

In today's digital landscape, maintaining the integrity and ownership of digital content is crucial across various fields, including the critical domain of medical applications. However, existing watermarking techniques face significant challenges, such as vulnerability to attacks and limitations in capacity and robustness. To address these challenges, this work presents a novel hybrid reversible watermarking approach utilizing the Lucas number series (LNS), normalization, and squint ternary least significant bit (STLSB). Additionally, the method incorporates a lightweight encryption technique based on homomorphic binomial coefficients (LHBC) to encrypt watermark images. The encrypted image is then embedded into the cover image at the STLSB position, specifically three bits from the left-most significant bit, resulting in a watermarked image. The Present issues in watermarking medical data include ensuring the watermark's robustness against attacks while maintaining data integrity and confidentiality, and balancing the need for traceability with the risk of compromising sensitive patient information. Experimental results show that the proposed method significantly improves embedding capacity by approximately 10% compared to existing techniques, achieving a PSNR of 52.0 dB, NCC of 1, SSIM of 0.9967, and consistently low BER, demonstrating enhanced robustness against various attacks, including JPEG compression, sharpening, resizing, and rotation. These findings highlight the method's effectiveness for secure medical image watermarking applications, ensuring integrity and confidentiality, and extending to practical uses in digital asset management, copyright protection, and authentication systems across diverse industries.