关于无线网络通信脆弱点实时提取仿真
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摘要
对无线网络的通信脆弱点进行提取,能够提高无线网络运行的整体安全性。对无线网络通信脆弱点的实时提取,需要通过滑动窗口历史的数据对脆弱点检测,对通信脆弱点的来源进行识别与验证,完成无线网络通信脆弱点的实时提取。传统方法以通信协议的脆弱点间隔训练的观测值,扩大模型训练的样本空间,但忽略了对脆弱点来源的验证,导致提取精度偏低。提出基于多模态的数据流的通信脆弱点的检测方法。利用多模态的数据流对通信脆弱点进行检测,对网络中时空的相关性进行应用,对节点中多模态的数据流的相关性进行研究,利用滑动窗口历史的数据对通信脆弱点进行异常检测,对通信脆弱点的来源进行识别与验证,完成对无线网络通信脆弱点实时提取。实验的结果表明,所提方法能有效的对通信脆弱点进行提取,提高了脆弱点检测准确率,并提高了网络运行的安全性。
Traditional extraction method for communication vulnerability of wireless network always ignores verification of vulnerability source,which leads to poor extraction precision. In order to overcome the defect,based on multi-modal data flow,a detection method for the communication vulnerability is presented. The multi-modal data flow was used to detect the communication vulnerability. Correlation of space time in network was applied. Correlation of the multi-modal data flow in node was studied. Anomaly detection was carried out for the communication vulnerability via historical data of sliding window. Identification and verification were carried out for the vulnerability source. Thus,real time extraction for the communication vulnerability was completed. Simulation results show that the method can extract the vulnerability effectively. It improves detection accuracy of the communication vulnerability and enhances security of network operation.
Traditional extraction method for communication vulnerability of wireless network always ignores verification of vulnerability source,which leads to poor extraction precision. In order to overcome the defect,based on multi-modal data flow,a detection method for the communication vulnerability is presented. The multi-modal data flow was used to detect the communication vulnerability. Correlation of space time in network was applied. Correlation of the multi-modal data flow in node was studied. Anomaly detection was carried out for the communication vulnerability via historical data of sliding window. Identification and verification were carried out for the vulnerability source. Thus,real time extraction for the communication vulnerability was completed. Simulation results show that the method can extract the vulnerability effectively. It improves detection accuracy of the communication vulnerability and enhances security of network operation.
引文
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[2]马媛媛,周诚,李千目.关于网络中入侵节点信息优化检测仿真研究[J].计算机仿真,2017,34(8):315-318.
[3]高华.网络入侵失稳控制时最优节点选择[J].沈阳工业大学学报,2017,39(1):94-98.
[4]肖阳,白磊,王仙.基于朋友机制的移动ad hoc网络路由入侵检测模型研究[J].通信学报,2015,36(s1):203-214.
[5]陈颖,等.基于耦合动态离散事件链相关性的信息网络异常检测初探[J].电力系统自动化,2016,40(17):38-43.
[6]赵悦,等.移动Ad-Hoc网络叶节点簇降低能源节约入侵检测[J].控制工程,2016,23(7):1137-1142.
[7]邱卫,等.基于改进遗传算法和隐Markov模型的协议异常检测方法[J].计算机应用研究,2016,33(4):1164-1168.
[8]万叶晶,叶继华,江爱文.一种基于时空相关性和异常检测的改进WSN节能策略[J].传感技术学报,2017,30(8):1267-1273.
[9]叶炼炼.基于随机空间树的数据流异常检测算法[J].计算机工程与设计,2017,38(9):2414-2419.
[10]王德文,杨力平.智能电网大数据流式处理方法与状态监测异常检测[J].电力系统自动化,2016,40(14):122-128.