Privacy-Preserving Data Sharing Framework for High-Accurate Outsourced Computation

被引:0
|
作者
Ma, Zhuoran [1 ,2 ,3 ]
Ma, Jianfeng [1 ,3 ]
Miao, Yinbin [1 ,2 ,3 ]
Liu, Ximeng [4 ,5 ]
Yang, Tengfei [1 ,3 ]
机构
[1] Xidian Univ, Sch Cyber Engn, Xian 710071, Shaanxi, Peoples R China
[2] State Key Lab Cryptol, POB 5159, Beijing 100878, Peoples R China
[3] Shaanxi Key Lab Network & Syst Secur, Xian, Shaanxi, Peoples R China
[4] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Fujian, Peoples R China
[5] Fujian Prov Key Lab Informat Secur Network Syst, Fuzhou 350108, Fujian, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
privacy-preserving; data sharing; outsourced computation; homomorphic encryption; rational number; FULLY HOMOMORPHIC ENCRYPTION; PUBLIC-KEY CRYPTOSYSTEM; EFFICIENT;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the advances of outsourced computation, the threats of data leakage and loss of computational accuracy over rational domain are attracting increasing concerns. In this paper, we propose a framework for Privacy-preserving Data Sharing and high-accurate outsourced Computation system, referred as PDSC. PDSC system can perform secure data sharing with multiple data providers. Besides, the original data and computed results in the rational field can be securely processed and stored in the cloud without privacy leakage. Specifically, we design privacy-preserving computation protocols over rational numbers to guarantee computational accuracy and handle outsourced operations on-the-fly. Detailed security analysis and experimental results demonstrate that PDSC system is secure and feasible, respectively.
引用
收藏
页数:6
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