Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 491-497.doi: 10.11896/jsjkx.201000169

• Information Security • Previous Articles     Next Articles

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).

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

CLC Number: 

  • 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] LIU Jie-ling, LING Xiao-bo, ZHANG Lei, WANG Bo, WANG Zhi-liang, LI Zi-mu, ZHANG Hui, YANG Jia-hai, WU Cheng-nan. Network Security Risk Assessment Framework Based on Tactical Correlation [J]. Computer Science, 2022, 49(9): 306-311.
[2] WU Gong-xing, Sun Zhao-yang, JU Chun-hua. Closed-loop Supply Chain Network Design Model Considering Interruption Risk and Fuzzy Pricing [J]. Computer Science, 2022, 49(7): 220-225.
[3] ZHAO Dong-mei, WU Ya-xing, ZHANG Hong-bin. Network Security Situation Prediction Based on IPSO-BiLSTM [J]. Computer Science, 2022, 49(7): 357-362.
[4] LYU Peng-peng, WANG Shao-ying, ZHOU Wen-fang, LIAN Yang-yang, GAO Li-fang. Quantitative Method of Power Information Network Security Situation Based on Evolutionary Neural Network [J]. Computer Science, 2022, 49(6A): 588-593.
[5] DU Hong-yi, YANG Hua, LIU Yan-hong, YANG Hong-peng. Nonlinear Dynamics Information Dissemination Model Based on Network Media [J]. Computer Science, 2022, 49(6A): 280-284.
[6] DENG Kai, YANG Pin, LI Yi-zhou, YANG Xing, ZENG Fan-rui, ZHANG Zhen-yu. Fast and Transmissible Domain Knowledge Graph Construction Method [J]. Computer Science, 2022, 49(6A): 100-108.
[7] ZHANG Shi-peng, LI Yong-zhong. Intrusion Detection Method Based on Denoising Autoencoder and Three-way Decisions [J]. Computer Science, 2021, 48(9): 345-351.
[8] WANG Jin-heng, SHAN Zhi-long, TAN Han-song, WANG Yu-lin. Network Security Situation Assessment Based on Genetic Optimized PNN Neural Network [J]. Computer Science, 2021, 48(6): 338-342.
[9] ZHANG Kai, LIU Jing-ju. Attack Path Analysis Method Based on Absorbing Markov Chain [J]. Computer Science, 2021, 48(5): 294-300.
[10] LIU Quan-ming, LI Yin-nan, GUO Ting, LI Yan-wei. Intrusion Detection Method Based on Borderline-SMOTE and Double Attention [J]. Computer Science, 2021, 48(3): 327-332.
[11] WANG Yu-chen, QI Wen-hui, XU Li-zhen. Security Cooperation of UAV Swarm Based on Blockchain [J]. Computer Science, 2021, 48(11A): 528-532.
[12] MA Lin, WANG Yun-xiao, ZHAO Li-na, HAN Xing-wang, NI Jin-chao, ZHANG Jie. Network Intrusion Detection System Based on Multi-model Ensemble [J]. Computer Science, 2021, 48(11A): 592-596.
[13] JIANG Jian-feng, SUN Jin-xia, YOU Lan-tao. Security Clustering Strategy Based on Particle Swarm Optimization Algorithm in Wireless Sensor Network [J]. Computer Science, 2021, 48(11A): 452-455.
[14] LIU Zhang-hui, ZHAO Xu, LIN Bing, CHEN Xing. Data Placement Strategy of Scientific Workflow Based on Fuzzy Theory in Hybrid Cloud [J]. Computer Science, 2021, 48(11): 199-207.
[15] BAI Xue, Nurbol and WANG Ya-dong. Map Analysis for Research Status and Development Trend on Network Security Situational Awareness [J]. Computer Science, 2020, 47(6A): 340-343.
Full text



No Suggested Reading articles found!