Malicious node detection model for wireless Mesh networks

YANG Hongyu; LI Hang

doi:10.16511/j.cnki.qhdxxb.2017.25.023

PDF(1363 KB)

Journal of Tsinghua University(Science and Technology) ›› 2017, Vol. 57 ›› Issue (7) : 687-694. DOI: 10.16511/j.cnki.qhdxxb.2017.25.023

COMPUTER SCIENCE AND TECHNOLOGY

Malicious node detection model for wireless Mesh networks

{{article.zuoZhe_EN}}

Author information +

History +

Abstract

Existing malicious node detection methods for wireless Mesh networks are not very efficient. This paper presents a malicious node detection method based on the mobile Ad-hoc networking (BATMAN) route protocol (MNDMB). The BATMAN route protocol is loaded into a wireless Mesh network in a source node message analysis module to generate the defection parameters and identify suspicious nodes depending on these parameters by comparisons to thresholds. Then, a multi-node voting mechanism is used to calculate the confidence value which is used as the criterion for judging the malicious node. Verification tests show that this protocol has higher detection rates and lower false positive rates in wireless Mesh networks than existing methods.

Key words

wireless Mesh network / network topology / malicious behavior / vote / confidence value

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

YANG Hongyu, LI Hang. Malicious node detection model for wireless Mesh networks[J]. Journal of Tsinghua University(Science and Technology). 2017, 57(7): 687-694 https://doi.org/10.16511/j.cnki.qhdxxb.2017.25.023

References

[1] 吴文甲, 杨明, 罗军舟. 无线Mesh网络中满足带宽需求的路由器部署方法 [J]. 计算机学报, 2014, 37(2): 344-355.WU Wenjia, YANG Ming, LUO Junzhou. A bandwidth-aware router placement scheme for wireless Mesh networks [J]. Chinese Journal of Computers, 2014, 37(2): 344-355. (in Chinese) [2] Banerjee U, Arya K, Gupta G, et al. Performance evaluation of an ant colony based routing algorithm in the presence of a misbehaving node [C]//Proceedings of the International Conference on Security of Internet of Things. New York, NY, USA: ACM, 2012: 227-233. [3] Priyanka J, Tephillah S, Balamurugan A. Malicious node detection using minimal event cycle computation method in wireless sensor networks [C]//Proceedings of the International Conference on Communications and Signal Processing. Piscataway, NJ, USA: IEEE, 2014: 905-909. [4] 张华鹏, 张宏斌, 葛娟, 等. Ad-hoc网络中基于信用的自私节点检测系统 [J]. 计算机工程, 2013, 39(6): 119-123.ZHANG Huapeng, ZHANG Hongbin, GE Juan, et al. Selfish node detection system based on credit in Ad-hoc network [J]. Computer Engineering, 2013, 39(6): 119-123. (in Chinese) [5] 陈波, 毛剑琳, 郭宁, 等. 基于K-means算法的无线传感器网络节点自私行为检测方法 [J]. 系统仿真学报, 2014, 26(3): 580-585.CHEN Bo, MAO Jianlin, GUO Ning, et al. Detection method for nodes selfish behavior of wireless sensor networks based on K-means algorithm [J]. Journal of System Simulation, 2014, 26(3): 580-585. (in Chinese) [6] 任智, 谭永银, 李季碧, 等. 可靠的机会网络自私节点检测算法 [J]. 通信学报, 2016, 37(3): 1-6.REN Zhi, TAN Yongyin, LI Jibi, et al. Reliable selfish node detection algorithm for opportunistic networks [J]. Journal on Communications, 2016, 37(3): 1-6. (in Chinese) [7] Liu Z, Dai J, Sheng Y, et al. A high-performance wireless Mesh network routing protocol [J]. Applied Mechanics & Materials, 2014, 513-517: 1705-1708. [8] Gupta S, Goel R. A graphical user interface framework for detecting intrusions using Bro IDS [J]. International Journal of Computer Applications, 2012, 55(13): 7-12. [9] Orosz P, Skopko T, Imrek J. Performance evaluation of the nano second resolution time stamping feature of the enhanced libpcap [C]//Proceedings of the Sixth International Conference on Systems and Networks Communications. Barcelona, Spain: ICSNC, 2011: 220-225. [10] 陈佩剑. 基于信任度量机制的入侵检测系统研究与实现 [D]. 长沙:国防科技大学, 2011.CHEN Peijian. The Study and Implementation of Honesty-rate Measurement Based on Intrusion Detection System [D]. Changsha: National University of Defense Technology, 2011. (in Chinese) [11] Lakshmi K, Reddy C. Efficient classifier generation over stream sliding window using associative classification approach [J]. International Journal of Computer Applications, 2015, 115(22): 1-9. [12] Tang H, Tang T, Zhang P. An adaptive Mesh redistribution method for nonlinear Hamilton-Jacobi equations in two-and three-dimensions [J]. Journal of Computational Physics, 2015, 188(2): 543-572.