网络入侵检测的多智能体模型

Said Ouiazzane, M. Addou, Fatimazahra Barramou
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引用次数: 11

摘要

本文的目的是提出一种基于多智能体系统的分布式入侵检测模型。多代理系统(multi Agent Systems, MAS)满足了网络和大数据问题对入侵检测系统的要求,非常适用于入侵检测系统。传统的入侵检测系统依赖于特征匹配来检测已知的攻击,而传统的入侵检测系统依赖于特征匹配来检测已知的攻击,MAS agent之间相互协作和通信,保证了在没有专家干预的情况下有效检测网络入侵。该模型通过响应网络在分布、自治、响应和通信方面的需求,帮助检测大型计算机基础设施中的已知和未知攻击。该模型利用多代理模型和Hadoop分布式文件系统(HDFS)实现了良好的实时入侵检测。
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A Multi-Agent Model for Network Intrusion Detection
The objective of this paper is to propose a distributed intrusion detection model based on a multi agent system. Mutli Agent Systems (MAS) are very suitable for intrusion detection systems as they meet the characteristics required by the networks and Big Data issues. The MAS agents cooperate and communicate with each other to ensure the effective detection of network intrusions without the intervention of an expert as used to be in the classical intrusion detection systems relying on signature matching to detect known attacks. The proposed model helped to detect known and unknown attacks within big computer infrastructure by responding to the network requirements in terms of distribution, autonomy, responsiveness and communication. The proposed model is capable of achieving a good and a real time intrusion detection using multi-agents paradigm and Hadoop Distributed File System (HDFS).
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