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The availability of bandwidth for internet access is sufficient enough to communicate digital assets. These digital assets are subjected to various types of threats.[19] As a result of this, protection mechanism required for the protection of digital assets is of priority in research. The threat of current focus is unauthorized copying of digital assets which give boost to piracy. This under the copyright act is illegal and a robust mechanism is required to curb this kind of unauthorized copy. To safeguard the copyright digital assets, a robust digital watermarking technique is needed. The existing digital watermarking techniques protect digital assets by embedding a digital watermark into a host digital image. This embedding does induce slight distortion in the host image but the distortion is usually too small to be noticed. At the same time the embedded watermark must be robust enough to with stand deliberate attacks. There are various techniques of digital watermarking but researchers are making constant efforts to increase the robustness of the watermark image. The layered approach of watermarking based on Huffman coding [5] can soon increase the robustness of digital watermark. [11] Ultimately, increasing the security of copyright of protection. The proposed work is in similar direction where in RMI (Random Matrix Image) is used in place of Huffman coding. This innovative algorithm has considerably increased the robustness in digital watermark while also enhancing security of production.

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As the (Covid-19) pandemic spreads, the creativity of the scientific community is thriving while trying to control the situation. They are trying to treat patients viably and work with the almost exhausted medical equipment and staff, while growing new, successful antibodies. Successful screening of SARS-CoV-2 empowers fast and proficient determination of COVID-19 and can relieve the weight on medical care frameworks. Numerous forecast models are being created to comprehend and prognosticate the spread of the pandemic and to stay away from the following wave. But in the coming time, we can be sure that the models would experience the ill effects of a few issues, security being one of them. All the models need to be built in such a way that the investigation task gets successfully conducted without compromising the privacy and security of the patients. To take care of this, we propose a blockchain framework for sharing patients’ personal data or medical reports. A blockchain will take care of the integrity part, but we still need to worry about confidentiality. Therefore, combining a genetic approach with a blockchain seemed like a good idea. A twofold hybrid methodology is proposed in this paper to tackle the issue of confidentiality. The outcomes displayed high entropy accomplishment for the utilized dataset. The sensitivity of the plaintext and ciphertext is also checked and compared with existing approaches which thus demonstrates the security of the proposed approach in the given setting.