一种基于El Gamal加密算法的压缩数据收集方法

doi:10.11959/j.issn.1000-0801.2019284

电信科学 ›› 2019, Vol. 35 ›› Issue (12): 67-78.doi: 10.11959/j.issn.1000-0801.2019284

一种基于El Gamal加密算法的压缩数据收集方法

虞晓韩¹,董克明²,李霞¹,陈超¹

¹ 浙江工商大学，浙江杭州 310018
² 云南财经大学，云南昆明 650221

修回日期:2019-12-10 出版日期:2019-12-20 发布日期:2020-01-15
作者简介:虞晓韩（1987- ），男，博士，浙江工商大学讲师，主要研究方向为无线传感器网络、压缩感知、数据收集和人工智能等|董克明（1986- ），男，博士，云南财经大学讲师，主要研究方向为无线传感器网络、数据挖掘和数据隐藏等|李霞（1988- ），女，博士，浙江工商大学讲师，主要研究方向为无线传感器网络、光传感器和可调带宽滤波器等|陈超（1986- ），男，博士，浙江工商大学副教授，主要研究方向为无线传感器网络、网络编码和机器学习等
基金资助:
国家自然科学基金资助项目(61701441);国家自然科学基金资助项目(61703368);国家自然科学基金资助项目(61801427);浙江省自然科学基金资助项目(LQ17F010001);浙江科技计划重点项目(2018C01084)

A compressive data gathering method based on El Gamal cryptography

Xiaohan YU¹,Keming DONG²,Xia LI¹,Chao CHEN¹

¹ Zhejiang Gongshang University,Hangzhou 310018,China
² Yunan University of Finance ＆Economics,Kunming 650221,China

Revised:2019-12-10 Online:2019-12-20 Published:2020-01-15
Supported by:
The National Natural Science Foundation of China(61701441);The National Natural Science Foundation of China(61703368);The National Natural Science Foundation of China(61801427);Zhejiang Provincial Natural Science Foundation(LQ17F010001);Key Projects of Zhejiang Science and Technology Plan(2018C01084)

摘要/Abstract

摘要：

压缩感知技术在信号处理、图像处理、数据收集与分析等方面有很大优势，是近年来的研究热点。研究了如何安全高效地运用压缩感知技术来收集无线传感器网络中的数据。传统的基于压缩感知技术的数据收集方法并不考虑数据收集的安全性，而且网络内的所有节点都会参与每个测量值的收集。将El Gamal加密算法和基于稀疏随机矩阵的压缩感知技术相结合，提出了一种基于El Gamal加密算法的稀疏压缩数据收集方法（El Gamal based sparse compressive data gathering，ESCDG）。理论分析和数值实验表明，ESCDG不仅能降低网络资源的消耗而且能抵御多项式算力的内部攻击和外部攻击。

关键词: 物联网, 数据收集, 压缩感知, 稀疏随机矩阵, 公钥加密

Abstract:

As a hot researching area,compressive sensing has advantages in signal process,image processing and data gathering and analysis.How to effectively and safely apply compressive sensing technology to collect data in wireless sensor networks is studied.Conventional compressive sensing technology based data collection method does not consider the security issue.Furthermore,every nod in the network must participate in the process of collecting measurements.The El Gamal cryptography and sparse matrices based compressive sensing technology were combined,and the El Gamal based sparse compressive data gathering (ESCDG) method was proposed.Theoretical analysis and numerical experiments show that ESCDG not only decreases the network resource consumption but also be able to defense the internal and external attacks.

Key words: IoT, data gathering, compressive sensing, sparse random matrix, public cryptography

中图分类号:

TP393

虞晓韩,董克明,李霞,陈超. 一种基于El Gamal加密算法的压缩数据收集方法[J]. 电信科学, 2019, 35(12): 67-78.

Xiaohan YU,Keming DONG,Xia LI,Chao CHEN. A compressive data gathering method based on El Gamal cryptography[J]. Telecommunications Science, 2019, 35(12): 67-78.

图/表 7

图1

图2

图3

图4

图5

图6

图7

参考文献 29

[1]	GUBBI J , BUYYA R , MARUSIC S ,et al. Internet of things (IoT):a vision,architectural elements,and future directions[J]. Future Generation Computer Systems, 2013,29(7): 1645-1660.
[2]	朱洪波, 杨龙祥, 于全 . 物联网的技术思想与应用策略研究[J]. 通信学报, 2010,31(11): 1-9.
	ZHU H B , YANG L X , YU Q . Investigation of technical thought and application strategy for the Internet of Things[J]. Chinese Journal of Communications, 2010,31(11): 1-9.
[3]	张建雄, 吴晓丽, 杨震 ,等. 基于工业物联网的工业数据采集技术研究与应用[J]. 电信科学, 2018,34(10): 124-129.
	ZHANG J X , WU X L , YANG Z ,et al. Research and application of industrial data acquisition based on industrial internet of things[J]. Telecommunications Science, 2018,34(10): 124-129.
[4]	宁焕生, 徐群玉 . 全球物联网发展及中国物联网建设若干思考[J]. 电子学报, 2010,38(11): 2590-2599.
	NING H S , XU Q Y . Research on global Internet of Things:developments and it’s construction in China[J]. Chinese Journal of Electronics, 2010,38(11): 2590-2599.
[5]	国务院. 关于深化“互联网+先进制造业”发展工业互联网的指导意见[R]. 2017.
	The State Council. Guidance on deepening the development of industrial internet in the “internet + advanced manufacturing industry”[R]. 2017.
[6]	PERERA C , ZASLAVSKY A , CHRISTEN P ,et al. Context aware computing for the internet of things:a survey[J]. IEEE Communications Surveys ＆ Tutorials, 2014(16): 414-454.
[7]	李锐君, 周伟, 侯维岩 . 面向先进制造环境的工业物联网关键技术研究[J]. 仪表技术, 2017(3): 4-7.
	LI R J , ZHOU W , HOU W Y . Research on the key technologies of the Industrial Internet of Things for the advanced manufacturing environment[J]. Instrumental Technology, 2017(3): 4-7.
[8]	湛锋, 秦冠军, 张长开 ,等. 若干SCADA监控系统的设计比较[J]. 工业控制计算机, 2018,31(2): 1-5.
	ZHAN F , QIN G J , ZHANG C K ,et al. Design comparison of several industrial monitoring SCADA systems[J]. Industrial Control Computer, 2018,31(2): 1-5.
[9]	陈海霞, 任庆海, 冯俊杰 . SCADA 系统在污水泵站中的应用[J]. 电子测试, 2018(1): 93-95.
	CHEN H X , REN Q H , FENG J J . Application of SCADA system in sewage pumping station[J]. Electronic Test, 2018(1): 93-95.
[10]	朱佳佳, 赵妍 . 物联网的应用与挑战[J]. 电信网技术, 2017(5): 26-30.
	ZHU J J , ZHAO Y . Applicatons and challenges in Internet of Things[J]. Telecommunications Network Technology, 2017(5): 26-30.
[11]	王清波 . 物联网安全挑战与关键技术分析[J]. 无线互联科技, 2019,16(1): 30-31.
	WANG Q B . Analysis on the security challenges and key technologies of Internet of Things[J]. Wireless Internet Technology, 2019,16(1): 30-31.
[12]	常洁, 王艺, 李洁 ,等. 工业通信网络现有架构的梳理总结和未来运营商的发展策略[J]. 电信科学, 2017,33(11): 121-133.
	CHANG J , WANG Y , LI J ,et al. Summary of existing framework in industrial communication networks and future development strategies for communication operators[J]. Telecommunications Science, 2017,33(11): 121-133.
[13]	XIE K , WANG X , LIU X ,et al. Interference-aware cooperative communication in multi-radio multi-channel wireless networks[J]. IEEE Transactions on Computers, 2016,65(5): 1528-1542.
[14]	WU D , ARKHIPOV D I , KIM M ,et al. ADDSEN:adaptive data processing and dissemination for drone swarms in urban sensing[J]. IEEE Transactions on Computers, 2017(66): 183-198.
[15]	LUO C , WW F , SUN J ,et al. Compressive data gathering for large-scale wireless sensor networks[C]// The 15th Annual International Conference on Mobile Computer Networking,Sep 20-25,2009,Beijing,China. New York:ACM Press, 2009: 145-156.
[16]	LUO J , XIANG L , ROSENBERG C . Does compressed sensing improve the throughput of wireless sensor networks[C]// The 44th IEEE International Conference on Communications,May 23-27,2010,Cape Town,South Africa. Piscataway:IEEE Press, 2010: 1-6.
[17]	EBRAHIMI D , ASSI C . On the interaction between scheduling and compressive data gathering in wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2016(15): 2845-2858.
[18]	ZHENG H , XIAO S , WANG X ,et al. Capacity and delay analysis for data gathering with compressive sensing in wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2013(12): 917-927.
[19]	ZHAO C , ZHANG W , YANG Y ,et al. Treelet-based clustered compressive data aggregation for wireless sensor networks[J]. IEEE Transactions on Vehicle Technology, 2015(64): 4257-4267.
[20]	HSIEH S H , HUNG T H , LU C S ,et al. A secure compressive sensing-based data gathering system via cloud assistance[J]. IEEE Access, 2018(6): 31840-31853.
[21]	CANDES E , WAKIN M . An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 2008(25): 21-30.
[22]	LI P , ZHANG C H , ZHANG T . Sparse recovery with very sparse compressed counting[J].,2013. arXiv preprint arXiv:1401.0201, 2013.
[23]	KATZ J , LINDELL Y . Introduction to modern cryptography[M]. New York: CRC PressPress, 2007.
[24]	YU X H , BAEK S J . Energy-efficient collection of sparse data in wireless sensor networks using sparse random matrices[J]. ACM Transactions on Sensor Networks, 2017,13(3):22.
[25]	YU X H , BAEK S J . Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency[J]. International Journal of Distributed Sensor Networks, 2017,13(10):1550147717737968.
[26]	GUPTA P , KUMAR P R . Critical power for asymptotic connectivity in wireless networks[M]// Stochastic Analysis,Control,Optimization and Applications. Birkh?user:Massachusetts Avenue, 1999: 547-566.
[27]	RAGHUNATHAN V , SCHURGERS C , PARK S ,et al. Energy-aware wireless microsensor networks[J]. IEEE Signal Processing Magazine, 2002,19(2): 40-50.
[28]	LIN X , LU R , HUAFEI Z ,et al. ASRPAKE:an anonymous secure routing protocol with authenticated key exchange for wireless ad hoc networks[C]// 2007 IEEE International Conference on Communications,Jun 24-28,2007,Glasgow,Scotland. Piscataway:IEEE Press, 2007: 1247-1253.
[29]	LIN Y H , CHANG S Y , SUN H M . CDAMA:concealed data aggregation scheme for multiple applications in wireless sensor networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2012,25(7): 1471-1483.

一种基于El Gamal加密算法的压缩数据收集方法

A compressive data gathering method based on El Gamal cryptography

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 29

相关文章 15

Metrics

推荐阅读 0

[1]	何耀宇, 张超. 面向无人机应用的低轨卫星通信技术适航分析[J]. 电信科学, 2023, 39(6): 96-104.
[2]	马天洋, 陈雄斌, 徐义武. 基于可见光通信的零能耗光标签[J]. 电信科学, 2023, 39(5): 20-27.
[3]	杜书, 马玫, 赵波, 曾琦, 刘星. 用于电力物联网随机接入的低碰撞跳频通信系统[J]. 电信科学, 2023, 39(1): 117-125.
[4]	马洪源, 周维, 付艳, 邵永平, 黎丹. 蜂窝物联网核心网目标架构演进探讨[J]. 电信科学, 2023, 39(1): 153-161.
[5]	郑师应, 李源, 杨博涵, 马帅, 肖善鹏. 5G+行业现场网技术与产业发展综述[J]. 电信科学, 2022, 38(Z1): 17-27.
[6]	汪晗, 刁磊, 王梦玲, 荣欣, 李佳珉, 尤肖虎. 工业物联网中URLLC的关键问题分析[J]. 电信科学, 2022, 38(Z1): 77-92.
[7]	王文哲, 安岗, 李忻, 张伟强, 刘振华, 郑念卿, 陈盛伟, 赵文东, 狄子翔, 顾照杰. 面向空天地一体化场景的5G卫星双模终端需求及应用探讨[J]. 电信科学, 2022, 38(Z1): 221-230.
[8]	陈楠, 赵建军, 钟平, 黄勇军, 陈天. 基于云原生的分布式物联网操作系统架构研究[J]. 电信科学, 2022, 38(7): 146-156.
[9]	李昕, 孙君. 基于价值差异学习的多小区mMTC接入算法[J]. 电信科学, 2022, 38(6): 82-90.
[10]	陈超杰, 谢伟, 何林巍, 田强, 贺润平, 王哲斐. 针对输电线路周边工程机械的防撞在线预警方法[J]. 电信科学, 2022, 38(5): 95-103.
[11]	杨震, 赵建军, 黄勇军, 李洁, 陈楠. 基于网络演进的人工智能技术方向研究[J]. 电信科学, 2022, 38(12): 27-34.
[12]	刘小忠, 方军予, 蒋永彬. 2G/3G转网视角下电信运营商物联网发展策略分析[J]. 电信科学, 2022, 38(10): 153-162.
[13]	丁铖, 陈锦荣, 曹小冬, 王翊. 基于服务质量的层次化结构资源分配算法[J]. 电信科学, 2022, 38(1): 102-111.
[14]	吴吉义, 李文娟, 曹健, 钱诗友, 张启飞, BUYYA Rajkumar. 智能物联网AIoT研究综述[J]. 电信科学, 2021, 37(8): 1-17.
[15]	瞿逢重, 来杭亮, 刘建章, 涂星滨, 姜园. 海洋物联网关键技术研究与应用[J]. 电信科学, 2021, 37(7): 25-33.