Next Generation Cloud Security: State of the Art Machine Learning Model
Sachi Nandan Mohanty, Gouse Baig Mohammad, Sirisha Potluri, Ponnada Naga Ramya, P. Lavanya · 2021
Recent days have seen an obvious shift in computing platforms and environments with the arrival of cloud computing. Most of the organizations moving towards cloud technology to satisfy varied user demands and requests, and to guard and safeguard the transactions and operations of the organizations. Over the cloud platforms, it is extremely essential to produce a secure and strong environmental support to ensure security and privacy. Machine learning (ML) based models have well-tried their significance to anticipate in finest outcomes to boost the choice of cloud based long-term course of actions. Efficient machine learning models have long been utilized in several application domains that required the identification and prioritization of adverse factors for a threat. The main objective of this paper is to propose a best strategic cloud security enhancement model for next generation computing standards. Efficient machine learning algorithms like convolution neural network gives automatic and responsive approaches to reinforce security in a cloud environment. These models give solutions that incorporate holistic approaches for secure enterprise knowledge throughout all the cloud applications.