Method of privacy protection based on multiple edge servers in personalized search - Qiang ZHANG; Guojun WANG; Shaobo ZHANG (Tongxin xuebao)
In the plaintext environment,users' personalized search results can be obtained through users' interest model and query keywords.However,it may possibly result in the disclosure of sensitive data and privacy,which prevents using sensitive data in cloud search.Therefore,data is generally stored in the form of ciphertext in the cloud server.In the process of cloud search service,users intend to quickly obtain the desired search results from the vast amount of ciphertext.In order to solve the problem,it was proposed that a method of privacy protection based on multiple edge servers in personalized search shall be used.By introducing multiple edge servers and cutting the index as well as the query matrix,the computing relevance scores of partial query and partial file index are achieved on the edge server.The cloud server only needs to get the relevance score on the edge server and make a simple processing that can return to the most relevant Top K files by user query,so as to make it particularly suitable for a large number of users in the massive personalized ciphertext search.Security analysis and experimental results show that this method can effectively protect users’ privacy and data confidentiality.In addition,it can guarantee high efficiency in search to provide better personalized search experience.