作者：王继营
作者单位：黄淮学院信息工程学院, 河南 驻马店 463000
关键词：移动无线传感网络;入侵检测;选择性转发攻击;低功耗网络路由;序贯概率比测试
摘要：
选择性转发攻击是对无线传感网络(wireless sensor networks,WSNs)最危险的攻击，特别是在移动环境的WSNs下。为此，针对基于IPv6的移动WSNs，对选择性转发攻击进行研究，并提出基于序贯概率比测试(sequential probability ratio test，SPRT)的检测算法(SPRT-DA)，该算法通过计算接受与丢失的数据包数识别恶意节点，并采用自适应的阈值机制排除恶意节点。实验数据表明，提出的SPRT-DA算法的检测率逼近100%。
A detection algorithm for selective forwarding attack in IPv6-based mobile wireless sensor networks
WANG Jiying
College of Information Engineering, Huanghuai University, Zhumadian 463000, China
Abstract: Selective forwarding attack is considered as the most dangerous attack in wireless sensor networks (WSNs), especially in mobile environment. To this end, the research on the selective forwarding attacks in IPv6-based mobile wireless sensor network is carried out and the sequential probability ratio test based detection algorithm(SPRT-DA) is proposed. This algorithm recognizes malicious nodes by calculating the number of received and lost packets and eliminates the malicious nodes combined with the self-adapting threshold mechanism. According to the experimental data, the detection rate of the SPRT-DA algorithm approaches 100%.
Keywords: mobile wireless sensor networks;intrusion detection;selective forwarding attack;low power and lossy networks;sequential probability ratio test
2018, 44(8): 120-124 收稿日期: 2017-12-25;收到修改稿日期: 2018-02-09
基金项目: 河南省科技厅发展计划项目(152102110039)
作者简介: 王继营(1975-),男,讲师,硕士,主要从事计算机网络及数据库方面的研究
参考文献
[1] GUBBI J, BUYYA, MARUSIC S, et al. Internet of things (iot):A vision, architectural elements, and future directions [J]. Future Generation Computer Systems, 2013, 3(7):23-31.
[2] MADHAV B, RALEGAONKAR A. Wireless sensor network[C]//International Journal of Computer Engineering Science (IJCES), 2012.
[3] SEN J. A survey on wireless sensor network security[C]//International Journal of Communication Networks and Information Security (IJCNIS), 2013.
[4] ZHOU H, WU Y, FENG L, et al. A security mechanism for clusterbased wsn against selective forwarding[J]. Sensors, 2016, 5(8):61-70.
[5] HU Y, WU Y, WANG H. Detection of insider selective forwarding attack based on monitor node and trust mechanism in wsn[J]. Wireless Sensor Network, 2014, 3(7):34-51.
[6] RUI S, WALLGREN L, VOIGT T. Sevelte:Real-time intrusion detection in the internet of things[J]. Ad Hoc Networks, 2015, 6(7):23-31.
[7] MOTAMEDI M, YAZDANI N. Detection of black hole attack in wireless sensor network using uav[C]//IKT20157th International Conference on Information and Knowledge Technology, 2015.
[8] 蔡绍滨, 韩启龙, 高振国, 等. 基于云模型的无线传感器网络恶意节点识别技术的研究[J]. 电子学报, 2012, 40(11):2232- 238.
[9] OBINNA I, OLUWASEYI A, TAREK S. Deinal of Service attack detection using dendritic cell algorithm[C]//2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, 2017.
[10] 周豫苹, 于冬梅, 陈群山, 等. 一类新的基于移动序贯测试的无线传感网络节点克隆攻击检测[J]. 传感技术学报, 2017, 6(8):935-943.
[11] LI H J, LI K Q, QU W Y. Secure and energy-efficient data aggregation with malicious aggregator identification in wireless sensor networks[J]. Future Genration Computer Systems, 2014, 37(7):108-116.
[12] HOW J W, WRIGHT M, DAS S K. Distributed detection of mobile malicious node attacks in wireless sensor networks[J]. Ad Hoc Networks, 2012, 10(3):512-523.
[13] 孙翠改, 钱素娟, 张军朝. 虚警率约束的联合弱分类器集成学习算法[J]. 计算机工程与设计, 2017, 12(4):3344-3348.
[14] KO J, CHANG M. Momoro:Providing mobility support for lowpower wireless applications[J]. IEEE Systems Journal, 2015, 9(2):585-594.
[15] SHIGEN S B, LIA Y J, XUA H Y. Signaling game based strategy of intrusion detection in wireless sensor networks[J]. Computers and Mathematics with Applications, 2014, 62(6):2404-2416.
