一种云环境下防火墙策略异常处理的优化方法

An Optimized Method of Solving Policy Anomalies in Firewall in Cloud Environment

针对传统防火墙策略异常处理方法在云环境下效率低的问题,提出一种基于规则风险值和堆排序的优化方法.基于CVSS通用漏洞评估系统标准,结合BP神经网络自学习原理,建立策略风险评估模型,计算规则的风险值.根据策略风险值优化冲突异常处理算法,并引入堆排序提高冗余异常处理的效率.对比实验表明,改进后的方法能很好地处理冲突异常和冗余异常,提高了防火墙效率.

Considering that the traditional method of solving policy anomalies in firewall is inefficient in cloud environment,the paper proposed an optimized method based on risk value of firewall rules and heap sort algorithm. One risk evaluation model is established to calculate the risk value of rule,using the combination of CVSS and BP neural network self-learning methods.According to risk value of firewall rules,the conflict abnormality will be solved,and the heap sort algorithm will be introduced to solve the redundant abnormality.The comparative experiments show that the improved method can well deal with conflict abnormality and redundant abnormality, improving the efficiency of the firewall.