摘要
为了完善防护体系、对恶意攻击做出准确预测,设计企业信息网络安全管理系统。该系统采用主动安全防御模式,选取随机森林算法客观评估网络安全态势感知,加快决策树生成随机森林的过程;将粒子群优化(PSO)算法融入支持向量机算法,使安全管理系统得到了稳定运行。实验结果证明,与其他算法相比,随机森林算法能够使模型预测更精确,改进的PSO算法对网络攻击的检测精度约为99%。
In order to improve the protection system and predict the malicious attack accurately,an enterprise information network security management system is designed.The system adopts the active security defense mode,selects the random forest algorithm to evaluate the network security situation awareness objectively,and speeds up the process of generating random forest from decision tree.The particle swarm optimization(PSO)algorithm is integrated into the support vector machine algorithm to make the security management system run stably.The experimental results show that the random forest algorithm can make the model prediction more accurate than other algorithms,and the accuracy of the improved PSO algorithm to detect network attacks is about 99%.
作者
王鑫
李坤
邱德熠
徐皓宇
WANG Xin;LI Kun;QIU Deyi;XU Haoyu(Chengdu Metro Operation Co.,Ltd.,Chengdu 610000,China)
出处
《微型电脑应用》
2024年第8期150-154,共5页
Microcomputer Applications
关键词
安全管理系统
随机森林算法
粒子群优化
支持向量机
网络安全态势感知
safety management system
random forest algorithm
particle swarm optimization
support vector machine
network security situation awareness
