面向雾增强型工业物联网的多维安全查询方案

周由胜; 谭畅; 唐飞

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

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面向雾增强型工业物联网的多维安全查询方案

学术论文 | 更新时间：2024-06-05

- 面向雾增强型工业物联网的多维安全查询方案
- Multi-dimensional secure query scheme for fog-enhanced IIoT
- 通信学报 2020年41卷第8期页码：175-186
- 作者机构：
  
  1. 重庆邮电大学计算机科学与技术学院，重庆 400065
  2. 重庆邮电大学网络空间安全与信息法学院，重庆 400065
- 作者简介：
  
  [ "周由胜（1979- ），男，湖北恩施人，博士，重庆邮电大学副教授，主要研究方向为数据安全、认证与密钥协商" ]
  [ "谭畅（1995- ），男，山东聊城人，重庆邮电大学硕士生，主要研究方向为安全查询、物联网安全等" ]
  [ "唐飞（1986- ），男，重庆垫江人，博士，重庆邮电大学副教授，主要研究方向为公钥密码理论与应用" ]
- 基金信息：
  
  国家自然科学基金资助项目(61702067)
- DOI：10.11959/j.issn.1000-436x.2020127
  中图分类号： TP309.2
- 网络出版日期：2020-08，
  
  纸质出版日期：2020-08-25
- 稿件说明：
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周由胜, 谭畅, 唐飞. 面向雾增强型工业物联网的多维安全查询方案[J]. 通信学报, 2020,41(8):175-186.

Yousheng ZHOU, Chang TAN, Fei TANG. Multi-dimensional secure query scheme for fog-enhanced IIoT[J]. Journal on communications, 2020, 41(8): 175-186.
周由胜, 谭畅, 唐飞. 面向雾增强型工业物联网的多维安全查询方案[J]. 通信学报, 2020,41(8):175-186. DOI： 10.11959/j.issn.1000-436x.2020127.

Yousheng ZHOU, Chang TAN, Fei TANG. Multi-dimensional secure query scheme for fog-enhanced IIoT[J]. Journal on communications, 2020, 41(8): 175-186. DOI： 10.11959/j.issn.1000-436x.2020127.

摘要

针对现有范围查询方案进行多维数据查询时缺乏隐私保护的问题，提出了一种带有隐私保护特性的面向雾增强型工业物联网多维安全查询方案。该方案首先将用户待查询的多个维度区间映射成一个查询矩阵；然后，构造辅助向量对查询矩阵进行分解，利用 BGN 同态加密对辅助向量进行处理形成查询陷门；最后，物联网设备终端利用同态特性将传感数据与查询陷门进行匹配。特殊辅助向量有效降低了方案空间复杂度，同态加密的自盲性保证了传感数据机密性和用户查询模式的隐私。仿真实验结果表明，所提方案的计算开销和通信开销较低。

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.

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references

CHOO K K R , LU R X , CHEN L Q , et al . A foggy research future:advances and future opportunities in fog computing research [J ] . Future Generation Computer Systems , 2018 , 78 ( 2 ): 677 - 679 .

LU R X , HEUNG K , LASHKARI A H , et al . A lightweight privacy-preserving data aggregation scheme for fog computing-enhanced IoT [J ] . IEEE Access , 2017 , 5 : 3302 - 3312 .

LU R , LIANG X H , LI X , et al . EPPA:an efficient and privacy-preserving aggregation scheme for secure smart grid communications [J ] . IEEE Transactions on Parallel and Distributed Systems , 2012 , 23 ( 9 ): 1621 - 1631 .

WANG J , YU X , ZHAO M . Privacy-preserving ranked multi-keyword fuzzy search on cloud encrypted data supporting range query [J ] . Arabian Journal for Science and Engineering , 2015 , 40 ( 8 ): 2375 - 2388 .

DAI H , YE Q Q , YI X , et al . VP2RQ:efficient verifiable privacy-preserving range query processing in two-tiered wireless sensor networks [J ] . International Journal of Distributed Sensor Networks , 2016 , 12 ( 11 ): 1 - 15 .

SHEN Y , HUANG L S , YANG W . Achieving personalized and privacy-preserving range queries over outsourced cloud data [C ] // 2017 IEEE International Conference on Communications . Piscataway:IEEE Press , 2017 : 1 - 6 .

LU R . A new communication-efficient privacy-preserving range query scheme in fog-enhanced IoT [J ] . IEEE Internet of Things Journal , 2018 , 6 ( 2 ): 2497 - 2505 .

BONEH D , GOH E J , NISSIM K . Evaluating 2-DNF formulas on ciphertexts [C ] // Theory of Cryptography Conference . Berlin:Springer , 2005 : 325 - 341 .

PAILLIER P , . Public-key cryptosystems based on composite degree residuosity classes [C ] // International Conference on the Theory and Applications of Cryptographic Techniques . Berlin:Springer , 1999 : 223 - 238 .

ISLAM M S , KUZU M , KANTARCIOGLU M . Inference attack against encrypted range queries on outsourced databases [C ] // Proceedings of the 4th ACM conference on Data and application security and privacy . New York:ACM Press , 2014 : 235 - 246 .

NAVEED M , KAMARA S , WRIGHT C V . Inference attacks on property-preserving encrypted databases [C ] // Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security . New York:ACM Press , 2015 : 644 - 655 .

KELLARIS G , KOLLIOS G , NISSIM K , et al . Generic attacks on secure outsourced databases [C ] // Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security . New York:ACM Press , 2016 : 1329 - 1340 .

LACHARITÉ M S , MINAUD B , PATERSON K G . Improved reconstruction attacks on encrypted data using range query leakage [C ] // 2018 IEEE Symposium on Security and Privacy . Piscataway:IEEE Press , 2018 : 297 - 314 .

DE C A , IOVINO V . jPBC:Java pairing based cryptography [C ] // 2011 IEEE symposium on computers and communication . Piscataway:IEEE Press , 2011 : 850 - 855 .

HUANG B , LIANG S . A range search scheme based on encrypted index hiding order and access patterns [C ] // 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber,Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) . Piscataway:IEEE Press , 2019 : 340 - 347 .

GUO C , ZHUANG R , JIE Y , et al . Secure range search over encrypted uncertain IoT outsourced data [J ] . IEEE Internet of Things Journal , 2018 , 6 ( 2 ): 1520 - 1529 .

BABU D S V . Efficient and privacy-preserving range query over outsourced cloud [D ] . Fredericton:Fredericton University of New Brunswick , 2018 .

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