This paper discusses a lightweight encryption-based secure digital watermarking technique for medical applications. The technique uses redundant discrete wavelet transform (RDWT) and singular value decomposition (SVD) along with nonsubsampled contourlet transform (NSCT) to improve robustness and imperceptibility. The security of the proposed technique is further improved by incorporating a lightweight (low-complexity) cryptographic mechanism that is applied after embedding multiple watermarks. The proposed scheme first partitions the host image into subcomponents and then calculates the entropy values for it. To the maximum entropy value, the NSCT is applied, followed by RDWT decomposition. Finally, SVD is applied to obtain a singular vector of RDWT-decomposed components. The watermark images are also processed using the same procedure mentioned above. The method uses singular values to hide watermarks into a host image. The experimental outcome shows that the combined technique makes our proposed approach more robust and imperceptible, while it is evaluated for various wavelet filters and 10 different types of medical and five different types of nonmedical cover images. Furthermore, the strength of the cryptographic mechanism is tested using standard performance measures and confirms its effectiveness in security. Moreover, it is evident from the results that our method shows improvement in robustness in comparison to previously reported techniques under consideration.
Recently, due to the increase in popularity of the Internet, the problem of digital data security over the Internet is increasing at a phenomenal rate. Watermarking is used for various notable applications to secure digital data from unauthorized individuals. To achieve this, in this article, we propose a joint encryption then-compression based watermarking technique for digital document security. This technique offers a tool for confidentiality, copyright protection, and strong compression performance of the system. The proposed method involves three major steps as follows: (1) embedding of multiple watermarks through non-sub-sampled contourlet transform, redundant discrete wavelet transform, and singular value decomposition; (2) encryption and compression via SHA-256 and Lempel Ziv Welch (LZW), respectively; and (3) extraction/recovery of multiple watermarks from the possibly distorted cover image. The performance estimations are carried out on various images at different attacks, and the efficiency of the system is determined in terms of peak signal-to-noise ratio (PSNR) and normalized correlation (NC), structural similarity index measure (SSIM), number of changing pixel rate (NPCR), unified averaged changed intensity (UACI), and compression ratio (CR). Furthermore, the comparative analysis of the proposed system with similar schemes indicates its superiority to them.
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