Recently, the Distributed Denial of Service (DDOS) attacks has been used for different aspects to denial the number of services for the end-users. Therefore, there is an urgent need to design an effective detection method against this type of attack. A fuzzy inference system offers the results in a more readable and understandable form. This paper introduces an anomaly-based Intrusion Detection (IDS) system using fuzzy logic. The fuzzy logic inference system implemented as a detection method for Distributed Denial of Service (DDOS) attacks. The suggested method was applied to an open-source DDOS dataset. Experimental results show that the anomaly-based Intrusion Detection system using fuzzy logic obtained the best result by utilizing the InfoGain features selection method besides the fuzzy inference system, the results were 91.1% for the true-positive rate and 0.006% for the false-positive rate.
翻译：最近,在拒绝向最终用户提供服务的数量方面,对不同方面都使用了分布式拒绝提供服务的攻击(DDOS),因此,迫切需要设计一种有效的检测方法来对付这种攻击。一个模糊的推断系统以更易读和易懂的形式提供结果。本文采用了一种基于异常的入侵探测系统(IDS),使用模糊的逻辑逻辑。作为分散式拒绝服务攻击(DDOS)的检测方法,实施了模糊逻辑推断系统。建议的方法应用于开放源代码DDDOS数据集。实验结果显示,使用模糊逻辑的异常入侵探测系统,除了使用模糊推断系统之外,通过使用InfoGain特征选择方法取得了最佳结果,真实阳性率为91.1%,假阳性率为0.006%。
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