计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 491-497.doi: 10.11896/jsjkx.201000169

• 信息安全 • 上一篇    下一篇

一个基于智能电网的跨层路由的信任评估协议

陈海彪1,2, 黄声勇1, 蔡洁锐1   

  1. 1 广东电网有限责任公司汕尾供电局信息中心 广东 汕尾516600
    2 华南理工大学计算机科学与工程学院 广州510641
  • 出版日期:2021-06-10 发布日期:2021-06-17
  • 通讯作者: 陈海彪(kuiha174@163.com)
  • 基金资助:
    国家自然科学基金资助项目(61771203,61803161)

Trust Evaluation Protocol for Cross-layer Routing Based on Smart Grid

CHEN Hai-biao1,2, HUANG Sheng-yong1, CAI Jie-rui1   

  1. 1 Guangdong Power Grid Co.,Ltd.,Shanwei Power Supply Bureau,Shanwei,Guangdong 516600,China
    2 School of Computer Science & Engineering,South China University of Technology,Guangzhou 510641,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:CHEN Hai-biao,born in 1971,bachelor,senior engineer.His main research interests include artificial intelligence and network security.
  • Supported by:
    National Natural Science Foundation of China(61771203,61803161).

摘要: 网络安全是智能电网通信网络设计中需要考虑的主要问题。但是,由于无线网络的开放性和不可预测性,因此容易受到攻击,尤其是利用漏洞在数据传输过程中发起跨层攻击。为了解决这一问题,提出了一种新的基于信任的路由框架,该框架利用贝叶斯推理计算直接信任,并利用D-S理论结合可靠邻居的证据计算间接信任,然后用层次分析法基于传输速率、缓冲容量和接收信号强度等跨层度量来计算节点的可信度。在仿真实验中,通过模拟恶意节点发起不同攻击的情况,对所提算法的性能进行了评估。仿真结果表明,该信任评估算法可以有效地抵抗恶意攻击,保证路由的安全性。

关键词: 贝叶斯理论, 层次分析, 跨层安全性, 模糊理论, 网络安全, 信任管理

Abstract: Network security is the main issue to be considered in the design of a smart grid communication network.However,due to the openness and unpredictability of wireless networks,they are vulnerable to attacks,especially exploiting vulnerabilities to launch cross-layer attacks during data transmission.In order to solve this problem,a new trust-based routing framework is proposed,which uses Bayesian inference to calculate direct trust and D-S theory combined with evidence of reliable neighbors to calculate indirect trust.Then it uses AHP to calculate the credibility of the node based on cross-layer metrics such as transmission rate,buffer capacity and received signal strength.In the simulation experiment,the performance of the proposed algorithm is eva-luated by simulating the situation that malicious nodes launch different attacks.Simulation results show that the trust evaluation algorithm can effectively resist malicious attacks and ensure the security of routing.

Key words: AHP, Bayesian theory, Cross-layer security, Fuzzy theory, Network security, Trust management

中图分类号: 

  • TP391
[1] 董一帆,熊荫乔,王宝耀.智能电网通信协议安全威胁与防御技术[J].计算机技术与发展,2019,29(2):1-6.
[2] 龙丹.面向智能电网通信的可靠路由研究[D].武汉:武汉科技大学,2019.
[3] LI Q,CAO G.Multicast authentication in the smart grid with one-time signature[J].IEEE Transaction Smart Grid,2011,2(4):686-696.
[4] 谢尧,吴柳,张思拓,等,.基于大数据的电力通信网的安全防护系统及实现[J].电子设计工程,2017,25(19):131-135.
[5] HAUSER C.Trust research to address uncertainty in security for the smart grid[C]//Innovative Smart Grid Technologies.2012:1-2.
[6] OTOUM S,KANTARCI B,MOUFTAH H.Hierarchical trust-based black-hole detection in WSN-based smart grid monitoring[C]//2017 IEEE International Conference onCommunications(ICC 2017).IEEE,Paris,France,2017:1-6.
[7] VELUSAMY D,PUGALENDHI G.An effective trust baseddefense mechanism to thwart malicious attack in smart grid communication network[C]//IEEE International Conference on Intelligent Techniques in Control.IEEE,Srivilliputhur,India,2017:1-9.
[8] OTOUM S,KANTARCI B,MOUFTAH H.Mitigating FalseNegative intruder decisions in WSN-based Smart Grid monitoring[C]//Wireless Communications & Mobile Computing Conference.IEEE,Valencia,2017:153-158.
[9] ALNASSER A,SUN H.A fuzzy logic trust model for securerouting in smart grid networks[J].IEEE Access,2017,5:17896-17903.
[10] XIANG M,BAI Q,LIU W.Trust-based Adaptive Routing forSmart Grid Systems[J].Journal of Information Processing,2014,22(2):210-218.
[11] GANESH KUMAR P,DURGADEVI V,ANAND P,et al.Fuzzy-based trusted routing to mitigate packet dropping attack between data aggregation points in smart grid communication network[J].Computing,2017,99(1):81-106.
[12] DURGADEVI V,GANESHKUMAR PANDGRID O.Fuzzy integrated Bayesian Dempster-Shafer Theory to defend cross-layer heterogeneity attacks in Communication Network of Smart Grid[J].Information Sciences,2019,479(4):542-566.
[13] WEI Z,TANG H,YUF R,et al.Security Enhancements for Mobile Ad Hoc Networks With Trust Management Using Uncertain Reasoning[J].IEEE Transactions on Vehicular Technology,2014,63(9):4647-4658.
[14] ASHTIANI M,AZGOMI M.A multi-criteria decision-makingformulation of trust using fuzzy analytic hierarchy process[J].Cognition,Technology and Work,2015,17(4):465-488.
[15] 田启华,黄超,于海东,等.基于AHP的耦合任务集资源分配权重确定方法[J].计算机工程与应用,2018,54(21):25-30,94.
[16] OBAYIUWANAE,FALOWO O.A multi MOORA approach to access network selection process in heterogeneous wireless networks[C]//2015 IEEE Science Technology & Innovation (AFRICON).Addis Ababa,Ethiopia,2015:1-5.
[17] 任云良.基于1-9标度法的交互性资产绩效管理评价体系[J].实验技术与管理,2017,34(11):259-262.
[18] YUAN Y,HUO L,WANG Z,et al.Secure APIT Localization Scheme against Sybil Attacks in Distributed Wireless Sensor Networks[J].IEEE Access,2018,6:27629-27636.
[1] 柳杰灵, 凌晓波, 张蕾, 王博, 王之梁, 李子木, 张辉, 杨家海, 吴程楠.
基于战术关联的网络安全风险评估框架
Network Security Risk Assessment Framework Based on Tactical Correlation
计算机科学, 2022, 49(9): 306-311. https://doi.org/10.11896/jsjkx.210600171
[2] 王磊, 李晓宇.
基于随机洋葱路由的LBS移动隐私保护方案
LBS Mobile Privacy Protection Scheme Based on Random Onion Routing
计算机科学, 2022, 49(9): 347-354. https://doi.org/10.11896/jsjkx.210800077
[3] 吴功兴, 孙兆洋, 琚春华.
考虑中断风险与模糊定价的闭环供应链网络设计模型
Closed-loop Supply Chain Network Design Model Considering Interruption Risk and Fuzzy Pricing
计算机科学, 2022, 49(7): 220-225. https://doi.org/10.11896/jsjkx.201100084
[4] 赵冬梅, 吴亚星, 张红斌.
基于IPSO-BiLSTM的网络安全态势预测
Network Security Situation Prediction Based on IPSO-BiLSTM
计算机科学, 2022, 49(7): 357-362. https://doi.org/10.11896/jsjkx.210900103
[5] 杜鸿毅, 杨华, 刘艳红, 杨鸿鹏.
基于网络媒体的非线性动力学信息传播模型
Nonlinear Dynamics Information Dissemination Model Based on Network Media
计算机科学, 2022, 49(6A): 280-284. https://doi.org/10.11896/jsjkx.210500043
[6] 陶礼靖, 邱菡, 朱俊虎, 李航天.
面向网络安全训练评估的受训者行为描述模型
Model for the Description of Trainee Behavior for Cyber Security Exercises Assessment
计算机科学, 2022, 49(6A): 480-484. https://doi.org/10.11896/jsjkx.210800048
[7] 吕鹏鹏, 王少影, 周文芳, 连阳阳, 高丽芳.
基于进化神经网络的电力信息网安全态势量化方法
Quantitative Method of Power Information Network Security Situation Based on Evolutionary Neural Network
计算机科学, 2022, 49(6A): 588-593. https://doi.org/10.11896/jsjkx.210200151
[8] 邓凯, 杨频, 李益洲, 杨星, 曾凡瑞, 张振毓.
一种可快速迁移的领域知识图谱构建方法
Fast and Transmissible Domain Knowledge Graph Construction Method
计算机科学, 2022, 49(6A): 100-108. https://doi.org/10.11896/jsjkx.210900018
[9] 张师鹏, 李永忠.
基于降噪自编码器和三支决策的入侵检测方法
Intrusion Detection Method Based on Denoising Autoencoder and Three-way Decisions
计算机科学, 2021, 48(9): 345-351. https://doi.org/10.11896/jsjkx.200500059
[10] 周仕承, 刘京菊, 钟晓峰, 卢灿举.
基于深度强化学习的智能化渗透测试路径发现
Intelligent Penetration Testing Path Discovery Based on Deep Reinforcement Learning
计算机科学, 2021, 48(7): 40-46. https://doi.org/10.11896/jsjkx.210400057
[11] 李贝贝, 宋佳芮, 杜卿芸, 何俊江.
DRL-IDS:基于深度强化学习的工业物联网入侵检测系统
DRL-IDS:Deep Reinforcement Learning Based Intrusion Detection System for Industrial Internet of Things
计算机科学, 2021, 48(7): 47-54. https://doi.org/10.11896/jsjkx.210400021
[12] 王金恒, 单志龙, 谭汉松, 王煜林.
基于遗传优化PNN神经网络的网络安全态势评估
Network Security Situation Assessment Based on Genetic Optimized PNN Neural Network
计算机科学, 2021, 48(6): 338-342. https://doi.org/10.11896/jsjkx.201200239
[13] 张凯, 刘京菊.
基于吸收Markov链的网络入侵路径分析方法
Attack Path Analysis Method Based on Absorbing Markov Chain
计算机科学, 2021, 48(5): 294-300. https://doi.org/10.11896/jsjkx.200700108
[14] 陈明豪, 祝跃飞, 芦斌, 翟懿, 李玎.
基于Attention-CNN的加密流量应用类型识别
Classification of Application Type of Encrypted Traffic Based on Attention-CNN
计算机科学, 2021, 48(4): 325-332. https://doi.org/10.11896/jsjkx.200900155
[15] 刘全明, 李尹楠, 郭婷, 李岩纬.
基于Borderline-SMOTE和双Attention的入侵检测方法
Intrusion Detection Method Based on Borderline-SMOTE and Double Attention
计算机科学, 2021, 48(3): 327-332. https://doi.org/10.11896/jsjkx.200600025
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!