Development of Security Clustering Process for Big Data in Cloud

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Abstract

Big data is a large volume of data that demands effective cost and novel forms of data to process for enhanced security imminent innovation, assessment creation, and optimization process. Cloud computing provides a consistent, fault lenient, and extensible background to the big data disseminated managing systems. Cloud computing is emerged that has a popular computing model of system of servers hosted over the Internet for the store, manage, and process the data. It includes several advantageous characteristics of cloud storage are easy to access, scalability, resilience, cost efficiency, and reliability of the data. Since every organization is moving its data to the cloud and uses the storage services provided by the cloud. However, threats to cloud security such as data loss, data breaches, insecure application programming interface, account or service traffic hijacking, denial of service, malicious insiders, shared technologies and dangers, insufficient diligence are moving the security of the data. So, it is essential to protect the information against denial of services, unauthorized access or modification of data. The proposed method provides the vital security for different environment to store and access the information file in big data cloud. A numerous levels of security services such as authorization, authentication, data integrity, and confidentiality are ensure by applying the proposed method; therefore, only the genuine users are allowable to store and access the data through this method. The proposed method has multiple levels of security such as authorization by the Cloud Service Provider, encryption of the data using different cryptographic algorithms though uploading the data to the cloud, and usage of one time password for decrypting the data while downloading it from the big data cloud.

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APA

Shrihari, M. R., Manjunath, T. N., Archana, R. A., & Hegadi, R. S. (2021). Development of Security Clustering Process for Big Data in Cloud. In Lecture Notes in Networks and Systems (Vol. 154, pp. 279–288). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-8354-4_29

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