WSNs入侵检测中实值否定选择算法研究

计算机工程与科学

WSNs入侵检测中实值否定选择算法研究

张凤斌，杨秋杰，席亮

（哈尔滨理工大学计算机科学与技术学院，黑龙江哈尔滨 150080）

收稿日期:2015-06-23 修回日期:2015-10-12 出版日期:2016-09-25 发布日期:2016-09-25
基金资助:
国家自然科学基金（61172168）；黑龙江省教育厅科学技术研究项目（12541130）

A real-value negative selection algorithm in WSNs intrusion detections

ZHANG Feng-bin,YANG Qiu-jie,XI Liang

（School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,China）

Received:2015-06-23 Revised:2015-10-12 Online:2016-09-25 Published:2016-09-25

摘要/Abstract

摘要：

针对无线传感器网络免疫入侵检测中否定选择算法采用r-连续位二进制串匹配度作为亲和力，检测率低且无法反映WSNs在一段时间内的动态特性这一现象，提出采用RNS-WSNs算法，该算法用一段时间内属性值的变化率构成向量作为抗原和抗体，通过计算向量间的曼哈顿距离作为亲和力。在NS3上模拟WSNs进行实验，结果显示在能量消耗相当且误报率相同的情况下，RNS-WSNs算法具有更高的检测率。

关键词: 无线传感器网络, 人工免疫, 否定选择, 实值

Abstract:

The negative selection algorithm in intrusion detections (IDs) for wireless sensor networks (WSNs) generally adopts the r-continuous binary string matching mechanism, which leads to low detection rate and cannot reflect the dynamic features of WSNs in a period of time. Aiming at the problem, we present a real-value negative selection algorithm called RNS-WSNs, which uses the change rate of the attribute value during an interval of time as the antigen and antibody, and the Manhattan distance between the two vectors as the affinity. Simulation results on network simulator 3 show that the real-value negative selection algorithm has higher detection rate under the same energy consumption and false positive rate.

Key words: wireless sensor networks (WSNs), artificial immune, negative selection, real-value

张凤斌，杨秋杰，席亮. WSNs入侵检测中实值否定选择算法研究[J]. 计算机工程与科学.

ZHANG Feng-bin,YANG Qiu-jie,XI Liang. A real-value negative selection algorithm in WSNs intrusion detections [J]. Computer Engineering & Science.

参考文献

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