基于混合深度学习模型的网络服务软件漏洞挖掘方法

Network service software vulnerability mining method based on hybrid deep learning model

为了提高网络服务软件的可靠性,提出基于混合深度学习模型的网络服务软件漏洞挖掘方法.分析网络服务软件漏洞特征,采用模糊信息聚类方法进行软件漏洞特征聚类,建立嵌入式多任务调度模型,结合多层指标参量约束控制方法进行网络服务软件漏洞检测,采用混合深度学习模型实现网络服务软件漏洞挖掘优化.仿真结果表明,采用该方法进行网络服务软件漏洞挖掘的准确性较高,提高了网络服务软件的可靠性.

In order to improve the reliability of network service software,a method of mining network service software vulnerabilities based on a hybrid deep learning model is proposed in this paper.The characteristics of network service software vulnerabilities are analyzed.According to the fuzzy information clustering method,the characteristics of software vulnerabilities are clustered.The embedded multi task scheduling model is established,which combined with multi-level index parameter constraint control method.The network service software vulnerability is detected according to the use of hybrid depth learning model and network service software vulnerability mining is optimized.The simulation results show that the method is more accurate and improves the reliability of network service software.