面向雾增强型工业物联网的多维安全查询方案

doi:10.11959/j.issn.1000-436x.2020127

Abstract

Abstract:

In view of the fact that most of the existing range query schemes for fog-enhanced IoT cannot achieve both multi-dimensional query and privacy protection,a privacy-preserving multi-dimensional secure query scheme for fog-enhanced IIoT was proposed.Firstly,the multiple ranges to be queried were mapped into a certain query matrix.Then,auxiliary vectors were constructed to decompose the query matrix,and then the auxiliary vector was processed by BGN homomorphic encryption to form a query trapdoor.Finally,with the homomorphic computation utilized by an IoT device terminal,the query trapdoor could be matched to its sensor data.Spatial complexity could be effectively reduced with the used specific auxiliary vectors.The confidentiality of sensor data could be ensured and the privacy of user’s query mode could be protected by the homomorphic encryption property.Experiments results show that the computational and communication costs are relatively low.

Key words: fog-enhanced, IIoT, secure query, privacy-preserving, BGN homomorphic encryption

CLC Number:

TP309.2

Yousheng ZHOU,Chang TAN,Fei TANG. Multi-dimensional secure query scheme for fog-enhanced IIoT[J]. Journal on Communications, 2020, 41(8): 175-186.

Figures/Tables 10

方案	原始数据加密阶段	陷门生成阶段	查询阶段
文献[7]方案	—	$10 k (⌈ \sqrt{l} ⌉ T_{o})$	2 kT _em+3 kT_p+kT_o
文献[15]方案	2klT_m+klT_o	4kT_m	2kT_m
文献[16]方案	2klT_o+klT_m	(2k+1)T_o	3kT_m+2kT_o
文献[17]方案	2klT_o+qT_em	5kT_m+6kT_o	2 kT _em+kT_p
本文方案	—	$(8 k + 2) ⌈ \sqrt{l} ⌉ (T_{o})$	2 kT _em+3 kT_p+kT_o

References 17

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参数	定义
α	查询陷门
σ	查询的匹配度，其值介于0到维度总数之间
γ	用户所发起查询的所在维度或物联网设备自
	身所在维度
β	查询偏移
ω	物联网设备反馈给雾设备的结果
ζ	雾设备向用户发送的查询结果
B_i	查询区间i的下界
T_i	查询区间i的上界
Build()	生成各类复合数据对象和向量等
Parse()	从各类复合数据对象和向量中提取数据

Multi-dimensional secure query scheme for fog-enhanced IIoT

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方案	通信开销/B
文献[7]方案	40 535
文献[15]方案	17 520
文献[16]方案	32 880
文献[17]方案	26 830
本文方案	33 751

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