Privacy-preserving large-scale systems of linear equations in outsourcing storage and computation

被引：0

作者：

Dongmei LI ^{[1
]}

Xiaolei DONG ^{[2
]}

Zhenfu CAO ^{[2
]}

Haijiang WANG ^{[1
]}

机构：

[1] Department of Computer Science and Engineering, Shanghai Jiao Tong University

[2] Shanghai Key Lab of Trustworthy Computing, East China Normal University

来源：

ScienceChina(InformationSciences) | 2018年 / 61卷 / 03期

基金：

中国国家自然科学基金; 高等学校博士学科点专项科研基金;

关键词：

cloud computing; privacy-preserving; linear equations; encryption; security;

D O I：

暂无

中图分类号：

TP309 [安全保密];

学科分类号：

081201 ; 0839 ; 1402 ;

摘要：

Along with the prevalence of cloud computing, it can be realised to efficiently outsource costly storage or computations to cloud servers. Recently, secure outsourcing mechanism has received more and more attention. We focus on secure outsourcing storage and computation for large-scale systems of linear equations(LEs) in this paper. Firstly, we construct a new efficient matrix encryption scheme. Then we exploit this encryption scheme to develop a new algorithm which can implement outsourcing storage and computation for large-scale linear equations in the semi-honest setting. Compared with the previous work,the proposed algorithm requires lower storage overhead and is with competitive efficiency.

引用

页码：148 / 156

页数：9

共 50 条

[21] Efficient Privacy-Preserving Large-scale CP Tensor Decompositions
Luo, Changqing
Salinas, Sergio
Li, Pan
2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2018,
[22] Privacy-Preserving Techniques for Protecting Large-Scale Data of Cyber-Physical Systems
Keshk, Marwa
Moustafa, Nour
Sitnikova, Elena
Turnbull, Benjamin
Vatsalan, Dinusha
2020 16TH INTERNATIONAL CONFERENCE ON MOBILITY, SENSING AND NETWORKING (MSN 2020), 2020, : 711 - 717
[23] Comment on "Efficient Secure Outsourcing of Large-Scale Sparse Linear Systems of Equations"
Cao, Zhengjun
Markowitch, Olivier
IEEE TRANSACTIONS ON BIG DATA, 2021, 7 (06) : 973 - 974
[24] Comment on "Harnessing the Cloud for Securely Outsourcing Large-Scale Systems of Linear Equations"
Cao, Zhengjun
Liu, Lihua
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2016, 27 (05) : 1551 - 1552
[25] Secure and efficient outsourcing computation on large-scale linear regressions
Yang, Yang
Xiong, Ping
Huang, Qing
Chen, Fei
INFORMATION SCIENCES, 2020, 522 : 134 - 147
[26] Cloud-Based Outsourcing for Enabling Privacy-Preserving Large-Scale Non-Negative Matrix Factorization
Fu, Anmin
Chen, Zhenzhu
Mu, Yi
Susilo, Willy
Sun, Yinxia
Wu, Jie
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2022, 15 (01) : 266 - 278
[27] Efficient Verifiable Outsourcing of Solving Large-Scale Linear Equations with Low Storage Overhead
Feng D.
Zhou F.
Wang Q.
Wu Q.
Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2019, 56 (05): : 1123 - 1131
[28] Applying the Trustworthy Remote Entity to Privacy-Preserving Multiparty Computation: Requirements and Criteria for Large-Scale Applications
Ankele, Robin
Kuecuek, Kubilay A.
Martin, Andrew
Simpson, Andrew
Paverd, Andrew
2016 INT IEEE CONFERENCES ON UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING AND COMMUNICATIONS, CLOUD AND BIG DATA COMPUTING, INTERNET OF PEOPLE, AND SMART WORLD CONGRESS (UIC/ATC/SCALCOM/CBDCOM/IOP/SMARTWORLD), 2016, : 414 - 422
[29] Privacy-Preserving Fair Outsourcing Polynomial Computation Without FHE and FPR
Wang, Ying
Wang, Qiang
Huang, Zhifan
Zhou, Fucai
Zhang, Changsheng
Bian, Che
MOBILE INTERNET SECURITY, MOBISEC 2023, 2024, 2095 : 78 - 93
[30] Privacy-Preserving and Verifiable Outsourcing Linear Inference Computing Framework
Liu, Jiao
Li, Xinghua
Liu, Ximeng
Tang, Jiawei
Wang, Yunwei
Tong, Qiuyun
Ma, Jianfeng
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 16 (06) : 4591 - 4604

← 1 2 3 4 5 →