针对IEEE 802.11协议的MAC层攻击存在多样化、智能化的情况,提出一种基于人工免疫的综合检测方法.针对恶意攻击记录每隔一定时间信道的传帧计数作为特征序列,采用滑窗双元累积算法检测;针对自私性攻击检测区分2种情况,即当检测节点处于饱和状态时,记录每个节点每隔一定时间传帧计数序列,采用残差阈值判别法进行初始检测,将检测到的自私节点的退避时间序列进行记录,并进一步进行编码和基因化处理作为基因检测体;当检测节点处于非饱和状态时采用基于相对位置的子串相关函数基因匹配检测.实验表明,该综合攻击检测方法达到了较低的误判率和较快的检测速度,提高了无线网络的可信性.%In view of the diversification and intelligentization of attack on MAC layer of MANET, an integrated detection method was presented based on the artificial immune. The research utilized the algorithm of slide - window dual cumulative (SW-DCUSUM) with the sequence of number of frames transmitted in signal channel as characteristics parameter to detect malicious behavior. In order to detect selfish behavior, two algorithms were proposed and used in two different cases respectively. Nodes saturated with traffic recorded the number of frames transmitted every a fixed time interval of every neighbor node and detected selfish attack based on slide-window-based residual error threshold ( SW-RET) algorithm, and the back off time of detected selfish node was further encoded into gene detector to facilitate further that the non-saturation nodes employed gene match algorithm to detect selfish attack based on the sub-string interrelated function of relative position. The simulation results showed that the detection based on artificial immune achieved low erroneous rate and high speed so improved the trustworthy of wireless networks.
展开▼
