Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.
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机译：当前，由于交通数据网络的速度提高以及对网络和计算机的攻击越来越多，入侵检测系统的处理时间和性能非常重要。已经提出了几种方法来解决这个问题，包括与几种算法混合。但是，本文旨在提出在多代理系统（MAS-IDS）中将改进的K均值与C4.5入侵检测系统混合的方法。 MAS-IDS由三个代理组成，即协调器，分析和通信代理。所使用的MAS的基本概念是将捕获的大型网络数据集划分为多个子集，然后根据数据网络大小和核心CPU可用性将其分配给多个代理。使用KDD Cup 1999数据集进行评估。在JADE平台上开发了提出的MAS中C4.5分类的混合修饰K均值。结果表明，与当前方法相比，MAS-IDS最多可将IDS处理时间减少70％，同时提高了检测精度。
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