基于ANFIS分类器的移动Ad-Hoc网络恶意节点检测系统

IF 1.1 Q3 CRIMINOLOGY & PENOLOGY
Gopalakrishnan Subburayalu, Hemanand Duraivelu, Arunprasath Raveendran, Rajesh Arunachalam, Deepika Kongara, C. Thangavel
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引用次数: 13

摘要

摘要提高无线移动自组网(MANET)的分组访问效率是实现高速数据传输的关键。由于感知区域内的恶意节点与可信节点具有相似的特性,因此由于恶意节点的识别会导致降级,降低严重程度将是一个复杂的问题。本文研究了基于自适应神经模糊推理系统(ANFIS)分类器的缺陷节点识别系统。利用ANFIS分类器对需要提取的可靠节点和恶意节点的定罪参数进行鉴定。在此基础上,采用分类器测试模式对MANET中的单个节点进行分类。随着恶意节点数量的增加,网络性能将会下降。由于网络中存在恶意节点,会导致报文投递率、吞吐量、检测率、能耗、精度值、链路故障等情况发生。采用优化节能路由协议(OEERP)、低能量自适应聚类层次协议(LEACH)、网络聚合中的数据路由(DRINA)和基站控制动态聚类协议(BCDCP)等保守技术,比较了预期的恶意节点检测结构。所提出的ANFIS分类器是在MATLAB中设计的,并可以使用c编程与NS2接口。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cluster Based Malicious Node Detection System for Mobile Ad-Hoc Network Using ANFIS Classifier
Abstract Improvement of efficient packet access in a wireless Mobile Ad-Hoc network (MANET) is vital for achieving high speed data rate. The degradation occurs due to identification of malicious node and hence, reducing the severity will be a complex problem due to similar characteristics with trusty nodes in sensing area. In this work, Adaptive Neuro Fuzzy Inference System (ANFIS) classifier based defected node identification system is developed. The conviction parameters to be extract of the reliable and malevolent nodes and these parameters are qualified by ANFIS classifier. Further, the individual nodes in MANET are classified in testing mode of classifier. The network performance will be degraded with the increased number of malicious nodes. Certain conditions like packet delivery ratio, throughput, detection rate, energy consumption, and precision value and link failures occur due to malicious node in the network. The anticipated malicious node detection structure be compare by means of the conservative techniques such as Optimized energy efficient routing protocol (OEERP), Low energy adaptive clustering hierarchy (LEACH), Data routing in network aggregation (DRINA)and Base station controlled dynamic clustering protocol (BCDCP). The proposed ANFIS classifier is designed in Matrix Laboratory (MATLAB) and it can be interfaced with NS2 using “c” programming.
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来源期刊
Journal of Applied Security Research
Journal of Applied Security Research CRIMINOLOGY & PENOLOGY-
CiteScore
2.90
自引率
15.40%
发文量
35
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