Name
Abstract | ||
|---|---|---|
In this paper, we mainly study the problem of computing the k nearest neighbor over the encrypted data. We solve this question from two aspects. Firstly, we focus on the query efficiency. It is necessary to improve the user experience and save computing resources through reducing query time. We propose a k nearest neighbor query algorithm based on hierarchical Clustering. This algorithm uses the pruning rules to exclude most of the non-nearest neighbor data and improve query efficiency. Secondly, considered from data's security, we use the SSED algorithm which can safely compute distance between two encrypted data by using the properties of homomorphic encryption algorithm. Then the SSED algorithm is combined with the hierarchical clustering algorithm to realize the computation of k nearest neighbors over the ciphertext. The experiments show that the algorithm proposed in this paper has high query efficiency. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CSCWD.2018.8465239 | 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design ((CSCWD)) |
Keywords | Field | DocType |
hierarchical clustering,k nearest neighbor,homomorphic encryption,encrypted data | k-nearest neighbors algorithm,Hierarchical clustering,Homomorphic encryption,Computer science,Euclidean distance,Encryption,Theoretical computer science,Ciphertext,Cluster analysis,Distributed computing,Computation | Conference |
ISBN | Citations | PageRank |
978-1-5386-1483-9 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiqiang Zhang | 1 | 162 | 23.92 |
| Lijie Xin | 2 | 0 | 0.34 |
| Xiaoqin Xie | 3 | 2 | 1.74 |
| Haiwei Pan | 4 | 52 | 21.31 |