Securing Private Cloud Using Deep Neural Network. Review Case

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Ohoud Alshabib ,Dr. Ayman Mohamed Mostafa

Abstract

Due to the commonness of public cloud, few research publications discuss the applicability of the proposed Deep Learning solutions to private cloud systems. Companies can now explore a wide variety of resources and applications, which were not possible a few short years ago. One of the most sought-after and sought-out resource is private cloud. Private cloud is a term that has come to represent the use of network computing for an exclusive, private use. Also, has opened up newer avenues for Distributed Denial of Service (DDoS) attacks. In this paper, we discussed how to access the security and protection of the private cloud from a type of DDoS attack using one of the deep learning algorithms, LSTM approach. Through this solution, we propose to protect the private cloud in the work environment of Google.

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How to Cite
Ohoud Alshabib ,Dr. Ayman Mohamed Mostafa. (2022). Securing Private Cloud Using Deep Neural Network. Review Case. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 13(03), 274–281. https://doi.org/10.17762/turcomat.v13i03.12954
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