Achieving Privacy-Preserving Multi Dot-Product Query in Fog Computing-Enhanced IoT

被引:0
|
作者
Mahdikhani, Hassan [1 ]
Lu, Rongxing [1 ]
机构
[1] Univ New Brunswick, Fac Comp Sci, Fredericton, NB E3B 5A3, Canada
关键词
Internet of Things; Fog computing; Privacy-preserving; Multi dot-product query; SECURE;
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
Fog computing-enhanced IoT (Internet of Things), as it can provide better IoT services at the network edge, has received considerable attention in recent years. In this paper, for this new paradigm, we present a new privacy-preserving multi dot-product query scheme, called PMQ, which enables the control center to gain k dot-product results simultaneously in one query. Specifically, in the proposed PMQ scheme, the BGN homomorphic encryption is employed for encrypting query request and response, and a fog device is deployed at the network edge to assist the privacy-preserving k dot-product query. Detailed security analysis shows that the proposed PMQ can achieve better privacy preservation, i.e., no information in query request and response will be disclosed. In addition, extensive simulations are conducted, and the results demonstrate that the proposed PMQ scheme can achieve acceptable efficiency in terms of communication overheads and computational costs.
引用
下载
收藏
页数:6
相关论文
共 50 条
  • [31] Enabling Robust and Privacy-Preserving Resource Allocation in Fog Computing
    Zhang, Lei
    Li, Jiangtao
    IEEE ACCESS, 2018, 6 : 50384 - 50393
  • [32] Practical Privacy-Preserving Federated Learning in Vehicular Fog Computing
    Li, Yiran
    Li, Hongwei
    Xu, Guowen
    Xiang, Tao
    Lu, Rongxing
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (05) : 4692 - 4705
  • [33] Collaborative Fog Computing Architecture for Privacy-Preserving Data Aggregation
    Qusa, Hani
    Tarazi, Jumana
    2021 IEEE WORLD AI IOT CONGRESS (AIIOT), 2021, : 86 - 91
  • [34] Privacy-preserving query over the encrypted image in cloud computing
    Zhu, Xudong
    Li, Hui
    Guo, Zhen
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2014, 41 (02): : 151 - 158
  • [35] Efficient Privacy-Preserving Spatial Data Query in Cloud Computing
    Miao, Yinbin
    Yang, Yutao
    Li, Xinghua
    Wei, Linfeng
    Liu, Zhiquan
    Deng, Robert H.
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2024, 36 (01) : 122 - 136
  • [36] Achieving Privacy-Preserving and Verifiable Data Sharing in Vehicular Fog With Blockchain
    Kong, Qinglei
    Su, Le
    Ma, Maode
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (08) : 4889 - 4898
  • [37] Achieving Practical and Privacy-Preserving kNN Query over Encrypted Data
    Zheng Y.
    Lu R.
    Zhang S.
    Shao J.
    Zhu H.
    IEEE Transactions on Dependable and Secure Computing, 2024, 21 (06) : 1 - 13
  • [38] PQuery: Achieving Privacy-Preserving Query with Communication Efficiency in Internet of Things
    Yekta, Nafiseh Izadi
    Lu, Rongxing
    2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2017,
  • [39] PMRQ: Achieving Efficient and Privacy-Preserving Multidimensional Range Query in eHealthcare
    Zheng, Yandong
    Lu, Rongxing
    Zhang, Songnian
    Guan, Yunguo
    Shao, Jun
    Wang, Fengwei
    Zhu, Hui
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (18) : 17468 - 17479
  • [40] Efficient privacy-preserving data replication in fog-enabled IoT
    Sarwar, Kinza
    Yongchareon, Sira
    Yu, Jian
    Rehman, Saeed Ur
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2022, 128 : 538 - 551