![]() |
个人信息Personal Information
副教授
博士生导师
硕士生导师
主要任职:无
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
办公地点:软件学院综合楼417
联系方式:liangzhao@dlut.edu.cn
A privacy-preserving high-order neuro-fuzzy c-means algorithm with cloud computing
点击次数:
论文类型:期刊论文
发表时间:2017-09-20
发表刊物:NEUROCOMPUTING
收录刊物:SCIE、EI、Scopus
卷号:256
期号:,SI
页面范围:82-89
ISSN号:0925-2312
关键字:Nuero-fuzzy c-means; Cloud computing; Heterogeneous data; Internet of Things; BGV
摘要:Currently, massive heterogeneous data is generating from the Internet of Things (IoT). Heterogeneous data processing with the neuro-fuzzy technology has become a hot topic for IoT. In this work, we propose a privacy-preserving high-order neuro-fuzzy c-means algorithm for clustering heterogeneous data (PPHOFCM) on cloud computing. PPHOFCM clusters the heterogeneous data set by representing each heterogeneous data object as a tensor and uses the tensor distance to capture the correlations in the high order tensor space. Furthermore, the cloud computing is employed to improve the clustering efficiency for massive heterogeneous data from IoT. The BGV encryption scheme is used to protect the private data when performing the high-order neuro-fuzzy c-means algorithm on cloud computing. Experiments are conducted on two real IoT datasets to verify the proposed algorithm. (C) 2017 Elsevier B.V. All rights reserved.