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

被引:0
|
作者
Dongmei Li
Xiaolei Dong
Zhenfu Cao
Haijiang Wang
机构
[1] Shanghai Jiao Tong University,Department of Computer Science and Engineering
[2] East China Normal University,Shanghai Key Lab of Trustworthy Computing
来源
关键词
cloud computing; privacy-preserving; linear equations; encryption; security;
D O I
暂无
中图分类号
学科分类号
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
收藏
相关论文
共 50 条
  • [31] Functional Privacy-preserving Outsourcing Scheme with Computation Verifiability in Fog Computing
    Tang, Wenyi
    Qin, Bo
    Li, Yanan
    Wu, Qianhong
    KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2020, 14 (01): : 281 - 298
  • [32] Functional privacy-preserving outsourcing scheme with computation verifiability in fog computing
    Tang, Wenyi
    Qin, Bo
    Li, Yanan
    Wu, Qianhong
    KSII Transactions on Internet and Information Systems, 2020, 14 (01) : 281 - 298
  • [33] Privacy-preserving fair outsourcing polynomial computation without FHE and FPR
    Wang, Qiang
    Wang, Ying
    Zhou, Fucai
    Xu, Jian
    Zhang, Changsheng
    COMPUTER STANDARDS & INTERFACES, 2025, 91
  • [34] A novel privacy-preserving outsourcing computation scheme for Canny edge detection
    Bowen Li
    Fazhi He
    Xiantao Zeng
    The Visual Computer, 2022, 38 : 4437 - 4455
  • [35] A novel privacy-preserving outsourcing computation scheme for Canny edge detection
    Li, Bowen
    He, Fazhi
    Zeng, Xiantao
    VISUAL COMPUTER, 2022, 38 (12): : 4437 - 4455
  • [36] SecHOG: Privacy-Preserving Outsourcing Computation of Histogram of Oriented Gradients in the Cloud
    Wang, Qian
    Wang, Jingjun
    Hu, Shengshan
    Zou, Qin
    Ren, Kui
    ASIA CCS'16: PROCEEDINGS OF THE 11TH ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, 2016, : 257 - 268
  • [37] Secure Index Construction for Privacy-Preserving Large-scale Image Retrieval
    Cheng, Bo
    Zhuo, Li
    Bai, Yu
    Peng, Yuanfan
    Zhang, Jing
    2014 IEEE FOURTH INTERNATIONAL CONFERENCE ON BIG DATA AND CLOUD COMPUTING (BDCLOUD), 2014, : 116 - 120
  • [38] Hierarchical infrastructure for large-scale distributed privacy-preserving data mining
    Wang, JL
    Xu, CF
    Shen, HF
    Pan, YH
    COMPUTATIONAL SCIENCE - ICCS 2005, PT 3, 2005, 3516 : 1020 - 1023
  • [39] Privacy-Preserving Proof of Storage in Large Group
    Ren, Yongjun
    Han, Jin
    Wang, Jin
    Fang, Liming
    49TH ANNUAL IEEE INTERNATIONAL CARNAHAN CONFERENCE ON SECURITY TECHNOLOGY (ICCST), 2015, : 269 - 272
  • [40] Secure Distributed Outsourcing of Large-scale Linear Systems
    Feng, Da
    Zhou, Fucai
    He, Debiao
    Guo, Mengna
    Wu, Qiyu
    2022 IEEE 42ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2022), 2022, : 1110 - 1121