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中文摘要：
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。
英文摘要：
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 detec- tion 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 be tween 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 posi-tive rate.
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