基于模糊关联规则挖掘改进算法的IDS研究

Research on IDS Based on Improved Algorithm for Mining Fuzzy Association Rules

由于现有入侵检测系统误报、漏报率较高,提高其检测准确率具有重要意义;阐述了模糊关联规则挖掘技术在网络入侵检测中发现网络异常并通过相似度计算做出量化的入侵响应的方法,详细描述了基于模糊关联规则算法的入侵检测的具体步骤,并改进了该算法的隶属度函数建立和标准规则集生成方法;通过异常检测实验验证了在入侵检测中应用这一算法的可行性,并且所做的改进可以提高算法的准确性,从而可以得出此改进算法较好地提高了入侵检测的准确率,为入侵检测系统的改进提供了一些思路。

As a result of high rate of misinformation and failing to report, It is very important to improve the nicety rate of IDS. This paper introduces the application of the technology of mining fuzzy association rules in intrusion detection, describes the process of IDS based on fuzzy association rules algorithm in detail and improves the approach of building the subjection degree function and creating the standard rules set in this algorithm. Using the experiment of anomaly detection, the feasibility of applying the algorithm in intrusion detection is validated. It is also proved that the improvements could advance the veracity of the algorithm. Accordingly this improved algorithm can improve the nicety rate of IDS preferably and provide some thought for the amelioration of IDS system.