多模态智慧网络信息云存储安全等级测试

Security Level Test of Multimodal Intelligent Network Information Cloud Storage

传统多模态智慧网络云存储安全测试方法忽略了对云图数字特征的修正,导致测试结果精度偏低、稳定性较差。于是提出新的多模态智慧网络信息云存储安全等级测试方法。明确云存储运行结构与安全检测机制,组建云存储安全等级测试指标体系并加以划分。利用贝叶斯算法构建反馈云模型,修正测试云图的数字特征,结合优化模糊综合测试法,确定测试指标的等级集合,计算集合内指标隶属度,得到存储安全等级模糊权向量集,完成安全等级测试。仿真结果证明,所提方法的云存储安全等级测试结果精确,稳定性强,具备显著的应用优势。

The correction of cloud image digital features affects the accuracy and stability of multimodal intelligent network cloud storage security test method. Therefore, a novel multi-modal intelligent network information cloud storage security level test method is designed. The cloud storage operation structure and security detection mechanism were determined to establish and divide the cloud storage security level test index system. Based on the Bayesian algorithm, a feedback cloud model was founded to correct the digital features of the test cloud image. According to the optimized fuzzy comprehensive test method, the level set of test indicators was determined, and the membership degree of indicators in the set was calculated, so as to obtain and store the fuzzy weight vector set of security level. Eventually, the security level test was completed. The simulation results show that this method has accurate cloud storage security level test results, excellent stability and remarkable applicability.