基于元数据管理的半结构化数据安全转换方法

Secure Conversion Method of Semi-Structured Data Based on Metadata Management

为了提升半结构化数据的安全转换能力、降低数据转换输出误码率(BER),提出基于元数据管理的半结构化数据安全转换方法。构建云存储动态半结构化数据的Hash编码模型,采用动态随机码元调制方法,分析云存储动态半结构化数据的参数统计特征量。采用模糊自相关融合调度方法,构建云存储动态半结构化数据的直觉模糊度对偶集。采用统计分析和概率密度特征采样的方法,构建云存储动态半结构化数据分簇聚类融合模型。采用元数据管理和参数模糊度辨识,实现半结构化数据安全转换和多属性群决策。根据分组交换的方法,实现云存储动态半结构化数据动态分析和聚类。结合信息聚类和自适应学习方法,实现半结构化数据安全转换和编码控制。仿真结果表明,采用该方法进行半结构化数据安全转换的准确性较高、数据输出误码率较低、融合性较好,提高了半结构化数据的安全传输能力。

To enhance the secure conversion of semi-structured data and reduce the data conversion output bit error rate(BER),a secure conversion method of semi-structured data based on metadata management is proposed.The Hash encoding model for dynamic the semi-structured data of cloud storage is constructed,and dynamic random code element modulation method is used to analyze the parameter statistical feature quantity of dynamic semi-structured data of cloud storage.The fuzzy autocorrelation fusion scheduling method is used to construct an intuitive fuzzy degree pairwise set of cloud storage dynamic semi-structured data.The statistical analysis and probability density feature sampling method are used to construct a cluster fusion model for cloud storage dynamic semi-structured data.Metadata management and parameter fuzziness identification are used to achieve secure conversion of semi-structured data and multi-attribute cluster decision making.According to the grouping exchange approach,dynamic analysis and clustering of cloud storage dynamic semi-structured data are realized.Combining information clustering and adaptive learning methods to achieve secure semi-structured data conversion and coding control.The simulation results show that the accuracy of semi-structured data secure conversion by this method is high,the data output BER is low,the convergence is good,and the secure conversion capability of semi-structured data is improved.