个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:软件学院、大连理工大学-立命馆大学国际信息与软件学院副院长
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:软件学院、国际信息与软件学院
学科:软件工程. 计算机应用技术
联系方式:guocheng@dlut.edu.cn
电子邮箱:guocheng@dlut.edu.cn
An Efficient Distributed Approach on High Dimensional Data Similarity Searchable Encryption
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论文类型:会议论文
发表时间:2018-01-01
收录刊物:CPCI-S
页面范围:1270-1275
关键字:searchable encryption; similarity search; high-dimensional; LSH; MapReduce
摘要:Due to the rapid development of cloud computing, how to perform efficient similarity retrieval on high-dimensional encrypted data has extensive application value. And because the data size that many applications are facing has grown at a geometric level, traditional centralized algorithms can not meet the needs of users. In this paper, we present a distributed similar searchable encryption scheme for high-dimensional data. Our method takes advantage of local sensitive hashing (LSH) to reduce the dimensions and make a fast similar neighbor searching. Then random vector dot product and homomorphic encryption techniques are used to design a specific encryption index structures so that a more rigorous privacy definition can be satisfied. The index building and searching algorithms are all implemented under the MapReduce framework to ensure the high scalability during processing of massive data. Through the analysis of experimental results of real data, the presented scheme can effectively perform similar retrieval on cipher text while protecting privacy.