基于协作信誉和设备反馈的物联网边缘服务器信任评估算法

doi:10.11959/j.issn.1000-436x.2022024

通信学报 ›› 2022, Vol. 43 ›› Issue (2): 118-130.doi: 10.11959/j.issn.1000-436x.2022024

基于协作信誉和设备反馈的物联网边缘服务器信任评估算法

张琳¹^,², 魏新艳¹, 刘茜萍¹, 黄海平¹^,², 王汝传¹^,²

¹ 南京邮电大学计算机学院，江苏南京 210003
² 江苏省无线传感网高技术研究重点实验室，江苏南京 210003

修回日期:2021-10-20 出版日期:2022-02-25 发布日期:2022-02-01
作者简介:张琳（1980-），女，江苏丰县人，博士，南京邮电大学副教授、硕士生导师，主要研究方向为网络安全、可信计算、隐私保护等
魏新艳（1993-），女，江苏宿迁人，南京邮电大学硕士生，主要研究方向为网络安全、可信计算等
刘茜萍（1981-），女，四川攀枝花人，博士，南京邮电大学副教授、硕士生导师，主要研究方向为分布式计算、服务计算等
黄海平（1981-），女，福建三明人，博士，南京邮电大学教授、博士生导师，主要研究方向为物联网、网络安全、隐私保护等
王汝传（1943-），男，安徽合肥人，南京邮电大学教授、博士生导师，主要研究方向为计算机软件、计算机网络和网格、信息安全、无线传感器网络等
基金资助:
国家自然科学基金资助项目(61572260);国家自然科学基金资助项目(61872196);国家自然科学基金资助项目(61872194);江苏省科技支撑计划基金资助项目(BE2017166)

Trust evaluation algorithm of IoT edge server based on cooperation reputation and device feedback

Lin ZHANG¹^,², Xinyan WEI¹, Xiping LIU¹, Haiping HUANG¹^,², Ruchuan WANG¹^,²

¹ College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
² Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China

Revised:2021-10-20 Online:2022-02-25 Published:2022-02-01
Supported by:
The National Natural Science Foundation of China(61572260);The National Natural Science Foundation of China(61872196);The National Natural Science Foundation of China(61872194);Scientific and Technological Support Project of Jiangsu Province(BE2017166)

摘要/Abstract

摘要：

针对边缘服务器的安全问题，提出了一种集成了服务器协作信誉以及设备用户反馈的信任评估算法来提高边缘计算上下文的安全性。交互过程中，使用了一种基于客观信息熵理论的融合算法来聚合服务器间的协作信誉，同时采用了部分同态加密算法来防止交互过程中用户数据的泄露。交互结束后，选择高可信的设备节点计算反馈信任，克服了传统机制的恶意反馈。在计算全局信任时，考虑了服务器的期望评分和自适应的权重计算算法，克服了传统信任方案的局限性。实验结果表明，所提信任度计算方案具有较低的时间复杂度和空间复杂度，并且可以有效抵抗恶意节点的攻击行为。

关键词: 物联网, 边缘服务器, 信誉, 反馈, 信任聚合

Abstract:

Aiming at the security problem of edge server, a trust evaluation algorithm was proposed, which integrated server cooperation reputation and device user feedback to improve the security of edge computing context.In the process of interaction, a fusion algorithm based on objective information entropy theory was used to aggregate the cooperation reputation between servers, and a partial homomorphic encryption algorithm was used to prevent the leakage of user data in the process of interaction.After the interaction, the highly trusted device node was selected to calculate the feedback trust, which overcame the malicious feedback of the traditional mechanism.When calculating the global trust, the expected score of the server and the adaptive weight calculation method were considered, which overcame the limitations of the traditional trust scheme.The experimental results show that the proposed trust calculation scheme has low time complexity and spatial complexity, and can effectively resist the attack of malicious nodes.

Key words: Internet of things, edge server, reputation, feedback, trust aggregation

中图分类号:

TP393

张琳, 魏新艳, 刘茜萍, 黄海平, 王汝传. 基于协作信誉和设备反馈的物联网边缘服务器信任评估算法[J]. 通信学报, 2022, 43(2): 118-130.

Lin ZHANG, Xinyan WEI, Xiping LIU, Haiping HUANG, Ruchuan WANG. Trust evaluation algorithm of IoT edge server based on cooperation reputation and device feedback[J]. Journal on Communications, 2022, 43(2): 118-130.

图/表 10

图1

图2

图3

表1

图4

图5

图6

图7

图8

图9

参考文献 29

[1]	SUN X , ANSARI N . EdgeIoT:mobile edge computing for the Internet of things[J]. IEEE Communications Magazine, 2016,54(12): 22-29.
[2]	SKALA K , DAVIDOVI? D , AFGAN E ,et al. Scalable distributed computing hierarchy:cloud,fog and dew computing[J]. Open Journal of Cloud Computing, 2015,2(1): 16-24.
[3]	SONEKAR S V , KSHIRSAGAR M M , MALIK L . Cluster head selection and malicious node detection in wireless ad hoc networks[C]// Next-Generation Networks. Berlin:Springer, 2018: 547-554.
[4]	YIM H J , SON Y H , LEE K C . A data distribution service quality of services policy configuration for data/events/services in the Internet of things[J]. Advanced Science Letters, 2016,22(11): 3612-3617.
[5]	乐光学, 戴亚盛, 杨晓慧 ,等. 边缘计算可信协同服务策略建模[J]. 计算机研究与发展, 2020,57(5): 1080-1102.
	YUE G X , DAI Y S , YANG X H ,et al. Model of trusted cooperative service for edge computing[J]. Journal of Computer Research and Development, 2020,57(5): 1080-1102.
[6]	HASHEM E M , NI Q , SHI Q . Secure and privacy-aware cloud-assisted video reporting service in 5G-enabled vehicular networks[J]. IEEE Transactions on Vehicular Technology, 2016,65(10): 7868-7881.
[7]	CONOSCENTI M , VETRò A , DE MARTIN J C . Peer to peer for privacy and decentralization in the Internet of things[C]// Proceedings of 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C). Piscataway:IEEE Press, 2017: 288-290.
[8]	JIN B , JIANG D S , XIONG J B ,et al. D2D data privacy protection mechanism based on reliability and homomorphic encryption[J]. IEEE Access, 2018,6: 51140-51150.
[9]	SCIANCALEPORE S , PIRO G , CALDAROLA D ,et al. OAuth-IoT:an access control framework for the Internet of things based on open standards[C]// Proceedings of 2017 IEEE Symposium on Computers and Communications. Piscataway:IEEE Press, 2017: 676-681.
[10]	GUAN Z T , SI G L , WU J ,et al. Utility-privacy tradeoff based on random data obfuscation in Internet of energy[J]. IEEE Access, 2017,5: 3250-3262.
[11]	ZHENG W T , WANG Z Y , LV T T ,et al. K-anonymity algorithm based on improved clustering[C]// Algorithms and Architectures for Parallel Processing. Berlin:Springer, 2018: 462-476.
[12]	WANG Q , HUANG J , CHEN Y J ,et al. PROST:privacy-preserving and truthful online double auction for spectrum allocation[J]. IEEE Transactions on Information Forensics and Security, 2019,14(2): 374-386.
[13]	WANG X , LUO T , LI J F . An efficient fully homomorphic encryption scheme for private information retrieval in the cloud[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2020,34(4): 2055008.
[14]	张佳乐, 赵彦超, 陈兵 ,等. 边缘计算数据安全与隐私保护研究综述[J]. 通信学报, 2018,39(3): 1-21.
	ZHANG J L , ZHAO Y C , CHEN B ,et al. Survey on data security and privacy-preserving for the research of edge computing[J]. Journal on Communications, 2018,39(3): 1-21.
[15]	HUANG X M , YU R , KANG J W ,et al. Distributed reputation management for secure and efficient vehicular edge computing and networks[J]. IEEE Access, 2017,5: 25408-25420.
[16]	邓宇乔, 杨波, 唐春明 ,等. 基于密文策略的流程加密研究[J]. 计算机学报, 2019,42(5): 1063-1075.
	DENG Y Q , YANG B , TANG C M ,et al. Research of ciphertext policy process-based encryption[J]. Chinese Journal of Computers, 2019,42(5): 1063-1075.
[17]	霍星, 张阳洋, 景永俊 ,等. MAS环境中一种基于反馈可信度的多维信誉计算算法[J]. 软件学报, 2020,31(2): 374-394.
	HUO X , ZHANG Y Y , JING Y J ,et al. Multidimensional reputation calculation method based on feedback reliability in MAS environment[J]. Journal of Software, 2020,31(2): 374-394.
[18]	王田, 张广学, 蔡绍滨 ,等. 传感云中的信任评价机制研究进展[J]. 通信学报, 2018,39(6): 37-51.
	WANG T , ZHANG G X , CAI S B ,et al. Survey on trust evaluation mechanism in sensor-cloud[J]. Journal on Communications, 2018,39(6): 37-51.
[19]	NAGARAJAN R , THIRUNAVUKARASU R , SHANMUGAM S . A fuzzy-based intelligent cloud broker with MapReduce framework to evaluate the trust level of cloud services using customer feedback[J]. International Journal of Fuzzy Systems, 2018,20(1): 339-347.
[20]	SIADAT S , RAHMANI A M , NAVID H . Identifying fake feedback in cloud trust management systems using feedback evaluation component and Bayesian game model[J]. The Journal of Supercomputing, 2017,73(6): 2682-2704.
[21]	邱磊, 蒋文贤, 李玉泽 ,等. 基于边缘计算与信任值的可信数据收集算法[J]. 软件学报, 2019,30(S1): 71-81.
	QIU L , JIANG W X , LI Y Z ,et al. Trustworthy data collection method based on edge computing and trust value[J]. Journal of Software, 2019,30(S1): 71-81.
[22]	LI X , LI J , YIU S ,et al. Privacy-preserving edge-assisted image retrieval and classification in IoT[J]. Frontiers of Computer Science, 2019,13(5): 1136-1147.
[23]	HAN G J , HE Y , JIANG J F ,et al. A synergetic trust model based on SVM in underwater acoustic sensor networks[J]. IEEE Transactions on Vehicular Technology, 2019,68(11): 11239-11247.
[24]	HUANG L T , DENG S G , LI Y ,et al. A trust evaluation mechanism for collaboration of data-intensive services in cloud[J]. Applied Mathematics ＆ Information Sciences, 2013,7(1L): 121-129.
[25]	WU Q T , ZHANG X L , ZHANG M C ,et al. Reputation revision method for selecting cloud services based on prior knowledge and a market mechanism[J]. The Scientific World Journal, 2014,2014: 1-9.
[26]	AZIZ B , FREMANTLE P , WEI R ,et al. A utility-based reputation model for the Internet of things[C]// ICT Systems Security and Privacy Protection. Berlin:Springer, 2016: 261-275.
[27]	REDDY V B , NEGI A , VENKATARAMAN S ,et al. A similarity based trust model to mitigate badmouthing attacks in Internet of things (IoT)[C]// Proceedings of 2019 IEEE 5th World Forum on Internet of Things. Piscataway:IEEE Press, 2019: 278-282.
[28]	YUAN J , LI X Y . A reliable and lightweight trust computing mechanism for IoT edge devices based on multi-source feedback information fusion[J]. IEEE Access, 2018,6: 23626-23638.
[29]	TRUONG N B , LEE G M , UM T W ,et al. Trust evaluation mechanism for user recruitment in mobile crowd-sensing in the Internet of things[J]. IEEE Transactions on Information Forensics and Security, 2019,14(10): 2705-2719.

符号	描述	取值
m	边缘设备个数	10 000
n	服务器个数	6
avg(\|F_i\|)	特定时间内反馈均值	1
?	反馈确定因子	0.4
pas	协作服务器占比	10%、20%、40%
md	恶意设备占比	10%、20%、40%
α	信誉的重要性	0.32

基于协作信誉和设备反馈的物联网边缘服务器信任评估算法

Trust evaluation algorithm of IoT edge server based on cooperation reputation and device feedback

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 29

相关文章 15

Metrics

推荐阅读 0

[1]	赵仕祺, 黄小红, 钟志港. 基于信誉的域间路由选择机制的研究与实现[J]. 通信学报, 2023, 44(6): 47-56.
[2]	金彪, 李逸康, 姚志强, 陈瑜霖, 熊金波. GenFedRL：面向深度强化学习智能体的通用联邦强化学习框架[J]. 通信学报, 2023, 44(6): 183-197.
[3]	田有亮, 吴柿红, 李沓, 王林冬, 周骅. 基于激励机制的联邦学习优化算法[J]. 通信学报, 2023, 44(5): 169-180.
[4]	张沛鑫, 张南, 王大庆, 吴桐, 李哲, 宫丰奎. 联合重采样的并行双反馈时频域符号定时恢复算法[J]. 通信学报, 2023, 44(4): 15-26.
[5]	田有亮, 田茂清, 高鸿峰, 何淼, 熊金波. 面向群智感知应用的基于协作的位置认证方案[J]. 通信学报, 2022, 43(9): 121-133.
[6]	王振宇, 郭阳, 李少青, 侯申, 邓丁. 面向轻量级物联网设备的高效匿名身份认证协议设计[J]. 通信学报, 2022, 43(7): 49-61.
[7]	周琮伟, 胡斌, 关杰. 基于全体圈个数为4的LFSR构造de Bruijn序列的研究[J]. 通信学报, 2022, 43(7): 126-133.
[8]	廖海君, 贾泽晗, 周振宇, 刘念, 王飞, 甘忠, 姚贤炯. 面向调控信息新鲜度保障的电力至简物联网资源优化[J]. 通信学报, 2022, 43(7): 203-214.
[9]	张勇, 李丹丹, 韩璐, 黄小红. 隐私保护的群体感知数据交易算法[J]. 通信学报, 2022, 43(5): 1-13.
[10]	杨小东, 田甜, 王嘉琪, 李梅娟, 王彩芬. 基于云边协同的无证书多用户多关键字密文检索方案[J]. 通信学报, 2022, 43(5): 144-154.
[11]	廖勇, 王世义. 高速移动环境下基于RM-Net的大规模MIMO CSI反馈算法[J]. 通信学报, 2022, 43(5): 166-176.
[12]	孙海丽, 龙翔, 韩兰胜, 黄炎, 李清波. 工业物联网异常检测技术综述[J]. 通信学报, 2022, 43(3): 196-210.
[13]	贾洪勇, 潘云飞, 刘文贺, 曾俊杰, 张建辉. 基于高阶异构度的执行体动态调度算法[J]. 通信学报, 2022, 43(3): 233-245.
[14]	廖勇, 程港, 李玉杰. 基于深度展开的大规模MIMO系统CSI反馈算法[J]. 通信学报, 2022, 43(12): 77-88.
[15]	张晓茜, 徐勇军. 面向零功耗物联网的反向散射通信综述[J]. 通信学报, 2022, 43(11): 199-212.