Sorting And Searching Method Of Encrypted Data Based On Mark Matching And Dimension Reduction Grouping

In recent years,cloud storage technology has developed rapidly and has been widely used in various industries.In order to reduce local storage space,users and enterprises turn to store data in the cloud.However,the cloud server can't guarantee the data security,and directly storing the data in the cloud may result in the disclosure of private information,so it is necessary to encrypt the data before uploading it.In order to protect the privacy of users and search the data in the cloud server according to the input keywords,searchable encryption technology appears.However,with the increase of data scale,the retrieval efficiency and security of cloud server are decreasing,and the existing methods can no longer meet the requirements.How to search encrypted data more safely and efficiently has become an urgent problem to be solved.For this reason,this paper proposes a grouping mark sorting search method based on encrypted cloud data(GMSM).Firstly,all documents are classified,then keywords are extracted and arranged in the order of categories to construct a dictionary,and then documents and query keywords are represented as vectors by vector space model.Secondly,the index and query mark are constructed.Because there is a certain correlation between query keywords,the corresponding query mark will be concentrated.Matching the correlation between query marks and index marks can filter a large number of irrelevant documents.Because these documents will no longer participate in scoring calculation,the search time is greatly reduced.In addition,by grouping the index vector and query vector according to the category of elements,the high-dimensional encryption key is transformed into multiple low-dimensional keys,thus reducing the encryption time.With the increasing number of documents,the dimension of index vector will increase continuously,which is still a big challenge to improve the efficiency of document encryption and search.In order to further improve,this paper proposes a grouping encryption sorting search method based on singular value decomposition(GESM).Before expanding and encrypting the index vector of a document,this method first expresses it as an index matrix,and then uses singular value decomposition algorithm to reduce the dimension of the index matrix.In order to reduce the dimension and ensure relatively high accuracy,threshold can be set to control the degree of dimension reduction.In addition,the index vector and query vector after dimension reduction are encrypted in groups,which not only reduces the search time,but also further reduces the encryption time,thus improving the efficiency.Finally,this paper analyzes the time complexity and privacy of the above scheme,and conducts experiments on this basis.The experimental results show that this scheme is feasible,and improves the encryption and search efficiency while ensuring security.