基于二进制粒子群的复杂网络攻击策略

Complex Network Attack Strategy Based on Binary Particle Swarm Optimization Algorithm

针对当前复杂网络攻击策略在选择攻击节点集上精准性不足,难以快速获取网络空间战场核心节点集以毁瘫敌方网络空间体系的问题,提出了基于二进制粒子群算法的攻击策略。该策略首先对网络节点状态进行编码,然后,计算基于深度优先搜索的适应度函数值,并使用二进制粒子群算法求解最优节点集,最后,针对典型网络模型开展仿真实验,对比分析了基于二进制粒子群算法的攻击策略和面向度(介数)的选择性攻击策略的性能和适应度,仿真表明,基于二进制粒子群算法的攻击策略具有高效性、有效性和普适性,可为指挥者提供辅助决策支撑。

Aiming at the current complex network attack strategy's insufficient accuracy in selecting the attack node set,and it is difficult to quickly obtain the core node set of the cyberspace battlefield to destroy the enemy's cyberspace system,an attack strategy based on binary particle swarm algorithm is proposed.In this strategy,firstly the state of the network nodes is encoded,then the fitness function value based on depth-first search is calculated,and the optimal node set is solved by using the binary particle swarm algorithm,finally a simulation experiment is carried out for the typical network models to compare and analyze the performance and adaptability of the binary particle swarm algorithm-based attack strategy and the degree-oriented(betweenness)selective attack strategy,simulation shows that the attack strategy based on binary particle swarm algorithm is efficient,effective and universal,and it can provide assistant decision support for the commander.