Modeling an intelligent risk assessment approach for cloud computing environment using artificial intelligence and supervised machine learning algorithms

The main pillar of today's competitive and future market is definitely to become cloud computing, and therefore companies use the capabilities of cloud computing services. To improve security initiatives by service cloud computing or CRP, new types of tools and protocols are always in demand. In order to develop a comprehensive risk assessment method, an extensive literature review was conducted to identify risk factors that may influence cloud computing adoption. In this context, various risk factors were identified. After feature selection and identification of risk factors, used to select the most effective features using linear regression algorithms. Then AI-ML techniques such as decision tree (DTC), random filter classifier, k-star with RMSE method are used. The analysis of threats in the CC environment showed the empirical results of dividing the data set into (۹۵%-۵%). It provides the best result from any remaining partitioning and in addition the proposed DTC algorithm provides the best results from the entire data set used in the test setup.

کلیدواژه ها:

Artificial intelligence ، Cloud computing (CC) ، Cloud security ، Machine learning ، Risk assessment