Privacy-Preserving Content-Aware Search Based on Two-Level Index

作     者：Zhangjie Fu Lili Xia Yuling Liu Zuwei Tian 

作者机构：School of Computer&SoftwareNanjing University of Information Science&TechnologyNanjing210044China College of Computer Science and Electronic EngineeringHunan UniversityChina School of Information Science and EngineeringHunan First Normal UniversityHunanChina 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2019年第59卷第5期

页      面：473-491页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work is supported by the National Natural Science Foundation of China under grant U1836110,U1836208,U1536206,61602253,61672294 by the National Key R&D Program of China under grant 2018YFB1003205 by China Postdoctoral Science Foundation(2017M610574) by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20181407 by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund by the Major Program of the National Social Science Fund of China(17ZDA092) Qing Lan Project by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China 

主　　题：Semantic search two-level index expanded central-keyword 

摘      要：Nowadays,cloud computing is used more and more widely,more and more people prefer to using cloud server to store ***,how to encrypt the data efficiently is an important *** search efficiency of existed search schemes decreases as the index *** solving this problem,we build the two-level ***,for improving the semantic information,the central word expansion is *** purpose of privacy-preserving content-aware search by using the two-level index(CKESS)is that the first matching is performed by using the extended central words,then calculate the similarity between the trapdoor and the secondary index,finally return the results in *** experiments and analysis,it is proved that our proposed schemes can resist multiple threat models and the schemes are secure and efficient.