基于特征节点分析的恶意节点检测算法研究

J4 ›› 2015, Vol. 37 ›› Issue (01): 78-83.

基于特征节点分析的恶意节点检测算法研究

谢晋阳1，李平1，谢桂芳2

（1.长沙理工大学计算机与通信工程学院，湖南长沙 410004;2.湘南学院计算机系,湖南郴州 423000)

收稿日期:2013-08-02 修回日期:2013-09-13 出版日期:2015-01-25 发布日期:2015-01-25
基金资助:
国家973计划资助项目（2011CB302902）；国家自然科学基金资助项目（61073180）

Study on the malicious nodes detection algorithm
based on feature nodes analysis

XIE Jinyang1,LI Ping1,XIE Guifang2

(1.School of Computer & Communication Engineering,
Changsha University of Science & Technology,Changsha 410004;
2.Department of Computer Science,Xiangnan University,Chenzhou 423000,China)

Received:2013-08-02 Revised:2013-09-13 Online:2015-01-25 Published:2015-01-25

摘要/Abstract

摘要：

无线传感器网络（WSN）通常部署在复杂的环境中，攻击者很容易通过俘获节点注入虚假数据，造成严重后果。提出基于对事件源能量感知值相近的特征节点的恶意节点检测机制（DAFNA），首先对事件源的能量值进行估计，且在此过程中过滤保留良性特征节点；然后以特征节点为参照建立坐标系，通过分析待检测节点与事件源的距离计算值与距离感知值之间的差异，进行恶意节点的判断；最后通过仿真实验，对算法性能进行分析，并与Hur算法对比，得出DAFNA算法所需先验知识少，恶意节点容纳度更好。

关键词: 无线传感器网络, 能量感知, 虚假数据, 特征节点, 恶意节点

Abstract:

Wireless Sensor Network (WSN) is usually deployed in complex environment, and an attacker can easily inject false data by capturing nodes, thus causing serious consequences. A malicious nodes detection algorithm based on feature nodes analysis (DAFNA) is proposed. Firstly, the energy values of the event sources are estimated, and nodes healthy characteristics are maintained in this process. Secondly, we establish coordinates according to the feature nodes, conduct a variance analysis of the calculated and perceived distances between the nodes to be detected and the event source, thus the malicious nodes are identified. Simulation result verifies the effectiveness of the proposed algorithm, and compared with Hur algorithm it has a better accommodation of malicious nodes while requiring less prior knowledge.

Key words: wireless sensor network(WSN);energyaware;false data;feature nodes;malicious nodes

谢晋阳1，李平1，谢桂芳2. 基于特征节点分析的恶意节点检测算法研究[J]. J4, 2015, 37(01): 78-83.

XIE Jinyang1,LI Ping1,XIE Guifang2. Study on the malicious nodes detection algorithm
based on feature nodes analysis [J]. J4, 2015, 37(01): 78-83.

参考文献

［1］Dong Huihui, Guo Yajun, Yu Zhongqiang, et al. A wireless sensor networks based on multiangle trust of node［C］∥Proc of 2009 International Forum on Information Technology and Applications, 2009:2831.
［2］Lindsey S, Raghavendra C, Sivalingam K M. Data gathering algorithms in sensor network using energy metrics ［J］．IEEE Transactions on Parallel and Distributed Systems, 2002, 13(9):924935.
［3］Ganeriwal S,Balzano L K,Srivastava M B.Reputationbased framework for high integrity sensor networks［J］. ACM Transactions on Sensor Networks, 2008, 4(3):137.
［4］Momani M, Agbinya J, Navarrete G P. A new algorithm of trust formation in wireless sensor networks［C］∥Proc of the 1st IEEE International Conference on Wireless Broadband and Ultra Wideband Communications (AusWireless ’06), 2006:16.
［5］da Silva A P R, Martins M H T, Rocha B P S, et al. Decentralized intrusion detection in wireless sensor networks［C］∥Proc of the 1st ACM International Workshop on Quality of Service & Security in Wireless and Mobile Networks, 2005:1623.
［6］Tseng ChinYang,Balasubramanyam P,Ko C,et al.A specificationbased intrusion detection system for AODV［C］∥Proc of the 1st ACM Workshop on Security of Ad Hoc and Sensor Networks, 2003:125134.
［7］Buchegger S, Boudec JeanYves L. The selfish node:Increasing routing security for mobile ad hoc networks［R］. RZ 3354(#93400). Switzerland:IBM Zurich Research Laboratory, 2001.
［8］Buchegger S, Boudec JeanYves L. Nodes bearing grudges:Towards routing security, fairness, and robustness in mobile ad hoc networks［C］∥Proc of the 16th Euromicro Conference on Parallel, Distributed and Networkbased Processing, 2008:403410.
［9］Buchegger S, Boudec JeanYves L. Performance analysis of the CONFIDANT protocol(Cooperation of nodes:Fairness in dynamic adhoc networks)［C］∥Proc of the 3rd ACM International Symposium on Mobile Ad Hoc Networking & Computing(MobiHOC), 2002:226236.
［10］Zhou Xingfeng. A study on ad hoc network intrusion detection system model based on credibility［D］. Nanjing:Nanjing University of Science and Technology, 2006.(in Chinese)
［11］PoWah Yau, Mitchell C J. Reputation methods for routing security for mobile ad hoc network［C］∥Proc of the 1st Workshop on Mobile Future and Symposium on Trends in Communications, 2003:130137.
［12］Hur J, Lee Y, Hong S M, et al. Trust management for resilient sensor networks［C］∥Proc of the ICISC’05, 2006:5668.
［13］Hur J, Lee Y, Yoon H, et al. Trust evaluation model for wireless sensor network［C］∥Proc of the ICACT’05, 2005:491496.
［14］Logan J D.Applied mathematics (a contemporary approach) ［M］. New York:Wiley, 1987.
附中文参考文献：
［10］周兴锋. 基于信任度AD HOC网络入侵检测系统模型研究［D］. 南京:南京理工大学, 2006.

[1]	罗仕杭, 何庆. 多策略融合改进的均衡优化算法及其应用[J]. 计算机工程与科学, 2023, 45(08): 1508-1520.
[2]	赵玉华, 贾向东, 胡海霞, 敬乐天. 无人机辅助的无线传感网络AoI最小化方案研究[J]. 计算机工程与科学, 2022, 44(07): 1216-1222.
[3]	张孟健, 汪敏, 王霄, 覃涛, 杨靖, . 混合粒子群-蝴蝶算法的WSN节点部署研究[J]. 计算机工程与科学, 2022, 44(06): 1013-1022.
[4]	高航, 吴嘉鑫, 陈龙, 武继刚. QoS保障下的无人机传感网安全通信路径规划[J]. 计算机工程与科学, 2022, 44(06): 1037-1045.
[5]	苟平章, 原晨, 张芬. 基于软件定义的WSNs非均匀分簇QoS路由算法[J]. 计算机工程与科学, 2022, 44(02): 227-236.
[6]	张晶, 魏淼, . 基于Delaunay三角划分策略的WSN区域覆盖优化研究[J]. 计算机工程与科学, 2021, 43(11): 1944-1951.
[7]	魏连锁, 陈齐齐, 韩建, 苏扬. 一种基于区域分裂与合并的势博弈网络拓扑控制算法[J]. 计算机工程与科学, 2021, 43(11): 2063-2068.
[8]	苟平章, 刘学治, 孙梦源, 何博. 基于跳距修正与狮群优化的WSNs三维定位算法[J]. 计算机工程与科学, 2021, 43(08): 1405-1412.
[9]	周静, 关玉蓉. 基于SDN的DWSN技术分析及性能优化研究[J]. 计算机工程与科学, 2021, 43(08): 1413-1421.
[10]	宋玲, 黄达胜. 一种基于狼群优化的改进DV_Hop定位算法[J]. 计算机工程与科学, 2021, 43(07): 1210-1218.
[11]	王俊喜, 陈桂芬. 能耗均衡的多跳多路径认知分层路由算法[J]. 计算机工程与科学, 2021, 43(03): 442-448.
[12]	张华南, 金红, 王峰. 无线传感器网络节能探索与研究[J]. 计算机工程与科学, 2021, 43(02): 295-303.
[13]	苟平章，张芬，毛刚，贾向东. 基于AGNES聚类的能耗均衡WSNs优化路由算法[J]. 计算机工程与科学, 2020, 42(04): 620-627.
[14]	胡震海，王立松. 抗窃听攻击的传感器网络空间范围聚集查询处理算法[J]. 计算机工程与科学, 2020, 42(01): 46-54.
[15]	张华南1,金红2. 基于连通支配集的无线传感器网络洪泛协议[J]. 计算机工程与科学, 2019, 41(12): 2143-2153.