Secured Cloud Computing for Data Management Using Big Data for Small and Medium Educational Institutions

Secured Cloud Computing for Data Management Using Big Data for Small and Medium Educational Institutions
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ISBN-10 : OCLC:1376802042
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Book Synopsis Secured Cloud Computing for Data Management Using Big Data for Small and Medium Educational Institutions by : Nupur Jain

Download or read book Secured Cloud Computing for Data Management Using Big Data for Small and Medium Educational Institutions written by Nupur Jain and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the recent past, the cloud computing plays vital role in educational institutions for improving business and service to students efficiently. The cloud computing is a standard methodology that gives accurate and efficient network for computational resources that can be useful for various educational institutions. The educational institutions should keep the data confident and higher range of security with privacy preservation. The management of big data in cloud is difficult to secure from risk and threats due to data exposure to many networks such as web, mobile communication, Internet of Things (IoT) and social media. The data storage in cloud safely and efficiently is the major challenging task in big data cloud computing. The major attention on cloud computing is the security issues could be associated with big data of educational institutions. In this paper, we have proposed data security approaches and methods in cloud to ensure the protection by highly minimizing risks and threats. We have discussed on efficient solution for cloud computing security issues to provide network security, data security and privacy preservation. The proposed methodology permits educational institutions to store data in the cloud assures safety and efficiency. It provides the solution to problem of big data security issues based on encryption and compression methodologies. The experimentation results show the proposed methodologies performance is accurate and efficient than existing systems.


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