【摘要】 为有效判断网络数据包是否存在被攻击的可能性,在以往研究的基础上,提出了一种DMPSO(detection method based on particle swarm optimization)检测算法。根据数据包属性的离散度定义状态检测指标;利用粒子群优化方法给出了标准差分布的计算流程,以判断数据包的异常状况;通过OPNET和MATLAB进行仿真实验,深入研究影响该算法的关键因素,对比其与其它算法间的性能状况,实验结果表明,DMPSO具有较好的适应性。更多还原

【Abstract】 To effectively determine the possibility of attacks for network packets,a new detection algorithm DMPSO(detection method based on particle swarm optimization)was proposed on the basis of previous studies.At first,the state indicators were defined with the discreteness of packet characteristic,and the calculation process of standard deviation distribution was presented to judge the packet anomaly by using particle swarm optimization.Finally,a simulation with OPNET and MATLAB was conducted to study the key factors of DMPSO.Compared to the performances of other algorithms,the results show that the proposed algorithm has better adaptability.更多还原