摘要
为了有效判断网络数据包是否存在被攻击的可能性,在以往的研究基础上提出了一种新的检测算法DMPSO。该算法根据数据包属性的离散度定义了状态检测指标,并利用粒子群优化方法给出了标准差分布的计算流程,以此判断数据包的异常状况。最后,进行仿真实验,对比了与其它算法之间的性能状况,结果表明DMPSO具有较好的适应性。
In order to effectively determine the possibility of attacks for network data packets, a new detection algorithm DMPSO （ Detection Method based of Particle Swarm Optimization） is proposed based previous studies. The state indicators are defined with the discreteness of packet characteristic in this algorithm, and the calculation process of standard deviation distribution is presented to judge the anomaly of packet by particle swarm optimization. Finally, a simulation is conducted. Compared to the performances of other algorithms, the results show that DMPSO has better adaptability.
出处
《四川理工学院学报（自然科学版）》
CAS
2014年第4期21-23,33,共4页
Journal of Sichuan University of Science & Engineering(Natural Science Edition)
基金
四川省教育厅重点项目(13ZA0118)
人工智能四川省重点实验室开放基金项目(2012RYY02)
四川理工学院培育项目(2012PY13)
企业信息化与物联网检测技术四川省高校重点实验室项目(2013WYJ01)
关键词
网络攻击
检测
变异算子
数据包
标准差
粒子群优化
cyber attack
detection
mutation operator
date packet
standard deviation
particle swarm optimization
