基于Apriori算法的一种改进异常入侵检测模型的研究

近年来网络入侵检测系统成为计算机系统安全架构的关键性问题。异常攻击检测效果差是现有系统目前遇到的首要问题。因此,基于数据挖掘技术提出一种模型来预测新颖的攻击并实时生成防火墙规则。运用了Apriori算法来创建一个自动防火墙规则发生器用以监测新的异常攻击。结果表明改进后的算法高效的提高异常入侵检测系统的性能。

Research of An Improved Model of Anomaly Intrusion Detection Based on Apriori Algorithm

In recent years,network intrusion detection system has become the key issues of computer system security architecture.Abnormal attack detection effect difference between the existing system is currently experiencing the most important issue.Therefore,proposed a model based on data mining to predict novel attacks and real-time generation of firewall rules.Use Apriori algorithm to create an automatic firewall rule generator for the monitoring of new abnormal attack.The results show that the improved algorithm is efficient to improve abnormal intrusion detection system performance.