The method selectively encodes information using privacy classification methods under timing constraints. Moreover, moving big data within different clouds that have different levels of sensitivity might expose important data to threats. Now think of all the big data security issues that could generate! The COVID-19 pandemic leads governments around the world to resort to tracking technology and other data-driven tools in order to monitor and curb the spread of SARS-CoV-2. We are committed to sharing findings related to COVID-19 as quickly as possible. Among the topics covered are new security management techniques, as well as news, analysis and advice regarding current research. In the following subsections, the details of the proposed approach to handle big data security are discussed. The security industry and research institute are paying more attention to the emerging security challenges in big data environment. 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Just Accepted. While opportunities exist with Big Data, the data can overwhelm traditional The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. Our proposed method has more success time compared to those when no labeling is used. The type of traffic used in the simulation is files logs. The MPLS header and labeling distribution protocols make the classification of big data at processing node(s) more efficient with regard to performance, design, and implementation. 51 Aradau, C and Blanke, T, “ The (Big) Data-security assemblage: Knowledge and critique ” (2015) 2 (2) Security Dialogue. Many recovery techniques in the literature have shown that reliability and availability can greatly be improved using GMPLS/MPLS core networks . 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