不定攻击中网络最弱节点定位技术仿真

发布时间：2018-06-29 06:43

本文选题：网络攻击 + 节点定位　；参考：《计算机仿真》2013年05期

【摘要】：快速查找攻击中的最弱节点能够更好的保证网络安全。传统的最弱节点定位方法在应用到随机攻击的状况下时,由于受攻击节点随机性增大,节点间的空间关联性迅速下降,攻击节点位置不定,因此很难对特定节点建立准确的约束模型,导致节点定位存在盲点,定位准确性较差。提出了一种改进粒子群节点特征寻优算法的不定网络攻击中最弱节点定位方法。计算网络节点之间的特征差值,在不定攻击中网络节点特征提取残差参数,进行极小化处理,通过设置粒子群中的每个粒子代表一个差异化节点定位的解,最大程度减小随机性带来的关联特征弱化问题。实验结果表明,利用改进后的算法进行不定攻击中网络最弱节点定位,能够有效提高节点定位的准确性,从而保证了网络的安全性。
[Abstract]:Fast lookup attack in the weakest node can better ensure network security. When the traditional weakest node localization method is applied to the random attack, the spatial correlation between the attacked nodes decreases rapidly, and the location of the attacking node is uncertain because of the increased randomness of the node under attack. Therefore, it is difficult to establish an accurate constraint model for specific nodes, which leads to blind spots and poor positioning accuracy. An improved particle swarm optimization (PSO) algorithm for locating the weakest nodes in uncertain network attacks is proposed. The feature difference between network nodes is calculated, and the residual parameters are extracted from the feature of the network nodes in the uncertain attack. Each particle in the particle swarm represents the solution of the location of a differentiated node by setting the particle swarm. To minimize the randomness of the associated feature weakening problem. The experimental results show that using the improved algorithm to locate the weakest nodes in the indeterminate attack can effectively improve the accuracy of node location and ensure the security of the network.
【作者单位】：山西大学商务学院;
【基金】：山西省自然科学基金项目(2010011022-1) 2011年度山西省高校科技开发项目(20111134) 2011年度山西省高等学校教学改革项目(J2011117) 2011年度山西大学商务学院科研基金项目(JG201102)
【分类号】：TP393.08

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