基于数据挖掘的云安全评估模型研究

为提高云安全评估的准确性，构建了云安全评估模型，分别从主机安全、数据安全、物理安全、网络安全和应用安全五个方面采用极限学习机数据挖掘算法获取评估证据，再使用隶属度方法进行数据的标准化和指标权重的计算，最终得到云安全评估结果。通过实验证明，构建的云安全评估模型能够快速获取云安全评估指标体系的评估证据，并科学的、综合地作出评估，体现了评估的全面性。

Research on Cloud Security Evaluation Model Based on Data Mining

To improve the accuracy of the safety assessment, this paper constructs the cloud security evaluation model. It obtains the  evidence of the evaluation respectively from the host security, data security, physical security, network security and application security, using limit of machine learning algorithm. Data mining and membership degree method is used for data standardization and index weight calculation, finally obtaining the cloud security assessment. The experiment proves that the constructed cloud security evaluation model can quickly obtain the evaluation evidence of the cloud security evaluation index system, and make the evaluation results scientifically and comprehensively, reflecting the comprehensiveness of the evaluation.