网络安全检测分解模型分析

网络的发展及网络规模的快速扩大,对网络安全管理带来了极大的挑战,其中人工智能已成为信息化的发展趋势。主要研究了网络安全检测模型行,在总结DoS/DDoS基本技术的基础上,对现有网络安全模型进行分析,据此完成了改进的网络安全模型的构建。对网络攻击行为应用支持向量机完成分类,同时采用了基于多个核函数的混合策略的算法,数据包通过改进的网络安全模型即可完成训练和测试。通过测试,结果表明提出的方法比传统软硬件相结合的网络防御系统更能满足网络的攻防需求,具有较高的实际应用价值,可以为网络安全检测模型的完善提供参考。

Analysis of Decomposition Model for Network Security Detection

The development of the network and the rapid expansion of the network scale have brought great challenges to the network security management.Artificial intelligence has become the development trend of informationization.This paper mainly studies the network security detection model.Based on the technology of DoS/DDoS,the existing network security model is analyzed,and the improved network security model is constructed accordingly.The classification process is completed by support vector machine and multiple kernel functions which are used to classify the network attack behaviors.The data packet can complete the training and testing processes through the improved network security model.The experimental results show that the method can better meet the network attack and defense needs comparing with the traditional software and hardware,and it improves the network defense system.The network security model has high practical application value and provides reference for the improvement of network security detection model.