ABSTRACT
Owing to the corona virus disease globally scientists designated as 'COVID -19 Pandemic', insurers have seen a rise in digital-virtual transactions as innovative and rejuvenation policy disbursements are made electronically in real-time, i.e., online. The lockdown and shutdown of schools, colleges and Academic institutions have shown chosen an advantage for education technology (EdTech) firms and enterprises, in conjunction with an expansion in need for their services and service sectors enabled by online payments. Many of the institutions are applying computational cloud mechanism to accumulate- build-up, store and share the data information related to the online transactions. Simultaneously, the rise of attacks and assaults is immensely amplified in the cloud mechanism. Keeping in view, scientists have developed model known as blockchain has been designed in a diverse and effective manner to overcome these raids and confrontations. But recent attacks on blockchain show that they can influence the blockchain and capture the half of the information from original transaction which can affect the integrity and privacy measure of the blockchain. The existing models are somewhat good but fail to offer continuous security because of the large data size. Therefore, in this paper, a novel blockchain-based cryptography algorithm is developed to secure blockchain transactions while avoiding security threats and preserving privacy. Moreover, the proposed blockchain algorithm is executed with the help of the Python platform. The performance of the proposed algorithm is compared with conventional techniques and attained the finest outcomes with high accuracy and less time duration. © 2022 IEEE.
ABSTRACT
Since the identification of the SARS-CoV-2, genus Beta-Coronavirus, in January 2020, the virus quickly spread in less than 3 months to all continents with a susceptible human population of about a 7.9billion, and still in active circulation. In the process, it has accumulated mutations leading to genetic diversity. Regular emergence of variants of concern/significance in different ecology shows genetic heterogeneity in the base population of SARS-CoV-2 that is continuously expanding with the passage of the virus in the vast susceptible human population. Natural selection of mutant occurs frequently in a positive sense (+) single-stranded (ss) RNA virus upon replication in the host. The Pressure of sub-optimal levels of virus-neutralizing antibodies and also innate immunity influence the process of genetic/ antigenic selection. The fittest of the mutants, that could be more than one, propagate and emerge as variants. The existence of different lineages, clades, and strains, as well as genetic heterogeneity of plaque purified virus population, justifies SARS-CoV-2 as 'Quasispecies‘ that refers to swarms of mutant sequences generated during replication of the viral genome, and all mutant sequences may not lead to virion. Viruses having a quasispecies nature may end up with progressive antigenic changes leading to antigenic plurality that is driven by ecology, and this phenomenon challenges vaccination-based control programs. © 2021, Editorial board of Journal of Experimental Biology and Agricultural Sciences. All rights reserved.