Research On Key Technologies Of Privacy Data Protection In Cloud Storage

With the development of cloud computing,cloud service platform has become the main carrier of various Internet products,helping enterprises to carry out data calculation,data analysis,data storage,etc.,which greatly reduces IT costs and improves the work efficiency.However,as a third-party service platform,the separation of data management rights and ownership make it not completely credible,and the user's privacy data is greatly threatened.On the promise of ensuring the security of private data,the efficiency of data access must also be guaranteed.While considering the security of framework,the security of data and integrity constraint are also the keys to protect big data privacy.Therefore,this thesis discusses and researches some key technologies of privacy data protection in cloud storage platform.A data preprocessing method based on the topic model will be proposed,and an efficient ciphertext retrieval scheme supporting multi keyword fuzzy semantic query and dynamic update will also be proposed.The main contents of this thesis are as follows:1)The data processing of the original plaintext documents to be retrieved mainly includes data preprocessing,the selection of the best number of topics,model analysis.Data preprocessing includes segmentation,stop-words removal,standardization,text feature extraction,etc.,and model analysis includes topic-keyword distribution extraction,document-topic distribution extraction and model evaluation.The purpose of data preprocessing is to reduce the dimension of the original plaintext document,accurately extract the subject-keyword distribution information and document-topic distribution information of the document,provide data support for the subsequent construction of an efficient multi-keyword cipher text retrieval scheme,and make subsequent searches more convenient and accurate.2)Construct the ciphertext retrieval scheme.The core idea of this step is to construct a secondary index based on the preprocessed data,that is,to construct a balanced binary tree index based on the topic-keyword distribution,and construct an inverted index based on the document-topic distribution.Based on this secondary index,this thesis constructs an efficient multi-keyword ciphertext retrieval scheme that supports dynamic updates and fuzzy matching.3)The experimental and theoretical analysis of the retrieval result set is carried out.By comparing the retrieval result set with the original document to be retrieved,the accuracy of the result set and the efficiency of the scheme are verified.The algorithm proposed in this thesis analyzes multiple sets of data,and compares the proposed scheme with other schemes.The scheme is compared in terms of performance and security.From the theoretical and comparative experiments,it verifies the efficiency,security and feasibility of the scheme proposed in this thesis.