公共云存储中私密数据的去重删除研究

Research on de-duplication deletion of private data in public cloud storage

为了降低公共云存储系统的空间开销,对公共云存储中私密数据的重复数据进行归并和删除处理,提高云存储容量,提出一种基于语义本体特征匹配检测的公共云存储中私密数据的去重删除技术。采用交叉分布方法进行公共云存储中私密数据的特征分解,根据数据的属性类别进行存储空间区域划分,提取私密数据的语义本体结构信息特征量,根据提取的特征量进行匹配检测,根据语义属性实现对重复数据的自适应筛选,对筛选出来的重复数据采用矩阵分解方法进行特征压缩和删减,实现去重删除。仿真结果表明,采用该算法进行公共云存储中私密数据的去重删除处理,提高了存储空间的容量,降低了数据存储的维数,实现了私密数据的优化存储。

In order to reduce the space overhead of the public cloud storage system,merge and delete the duplicate data among private data in public cloud storage,and improve the cloud storage capacity,a de-duplication deletion technology of private data in public cloud storage is proposed,which is based on the semanteme ontology feature matching. The cross-distribution method is used to perform the feature decomposition of the private data in public cloud storage,with which the storage space region is divided according to the data attribute category,and the characteristic quantity of the semantic ontology structure information of the private data is extracted to carry out the matching detection. The duplicated data is adaptively screened according to the semantic property,and performed with feature compression and deletion with matrix decomposition method to realize the deduplication deletion. The simulation results show that the algorithm used to realize the de-duplication deletion of the private data in public cloud storage can improve the capacity of storage space,reduce the dimension of data storage,and realize the optimization storage of private data.