A new secure arrangement for privacy-preserving data collection

被引:25
作者
Song, Jingcheng [1 ]
Han, Zhaoyang [2 ]
Wang, Weizheng [3 ]
Chen, Jingxue [4 ]
Liu, Yining [5 ]
机构
[1] Guilin Univ Elect Technol, Sch Informat & Commun, Guangxi Key Lab Trusted Software, Guilin 541004, Guangxi Zhuang, Peoples R China
[2] Univ Aizu, Informat Comp Sci, Aizuwakarnatsu, Fukushima 9650006, Japan
[3] City Univ Hong Kong, Comp Sci Dept, Hong Kong 999077, Peoples R China
[4] Univ Elect Sci & Technol China, Sch Informat & Software Engn, Chengdu 610054, Sichuan, Peoples R China
[5] Guilin Univ Elect Technol, Sch Comp Sci & Informat Secur, Guangxi Key Lab Trusted Software, Guilin 541004, Guangxi Zhuang, Peoples R China
基金
中国国家自然科学基金;
关键词
Privacy; Secure arrangement; Data collection; Aggregation; BIG DATA; EFFICIENT; SCHEME; MODEL;
D O I
10.1016/j.csi.2021.103582
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A big number of users' healthy data are necessary for the Internet of Things (IoT) healthcare. Therefore, the institutions, which have access to more data can provide better medical services such as more accurate diagnosis. However, privacy is often a bottleneck for IoT healthcare. Users often refuse to provide their health data based on privacy considerations. To balance the requirement of data collection and personal privacy, a lot of privacy preserving data collection schemes are provided. A very important work of these schemes is to produce a secret position for every user to store her/his data, which is named secure arrangement. A novel secure arrangement method is proposed in this paper, which is based on matrix eigenvalue calculation. Compared with the current secure arrangement methods, the proposed method is more robust and efficient, which drives the proposed scheme to be more suitable for repeated aggregation. Then we use an example to illustrate how to use the proposed arrangement method to construct a privacy data collection protocol. We prove the proposed scheme is secure and efficient in security analysis and efficiency analysis.
引用
收藏
页数:8
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