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Application of Fuzzy Logic for Distributed Intrusion Detection

机译:模糊逻辑在分布式入侵检测中的应用

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Application of agent technology in Intrusion Detection Systems (IDSs) has been developed. Intrusion Detection (ID) agent technology can bring IDS flexibility and enhanced distributed detection capability. However, the security of the ID agent and methods of collaboration among ID agents are important problems noted by many researchers. In this paper, coordination among the intrusion detection agents by Blackfioard Architecture (BBA), which transcends into the field of distributed artificial intelligence, is introduced. A system using BBA for information sharing can easily be expanded by adding new agents and increasing the number of BlackBoard (BB) levels. Moreover the subdivided BB levels enhance the sensitivity of ID. This paper applies fuzzy logic to reduce the false positives that represent one of the core problems of IDS. ID is a complicated decision-making process, generally involving enormous factors regarding the monitored system. A fuzzy logic evaluation component, which represents a decision agent model of in distributed IDSs, considers various factors based on fuzzy logic when an intrusion behavior is analyzed. The performance obtained from the coordination of an ID agent with fuzzy logic is compared with the corresponding non-fuzzy type ID agent.
机译:制定了代理技术在入侵检测系统(IDS)中的应用。入侵检测(ID)代理技术可以带来IDS灵活性和增强的分布式检测能力。然而,ID代理的安全性和ID代理之间的协作方法是许多研究人员注意到的重要问题。在本文中,介绍了Blackfioard架构(BBA)的入侵检测代理的协调,它超越分布式人工智能领域。通过添加新代理并增加黑板(BB)级别,可以轻松扩展使用BBA进行信息共享的系统。此外,细分的BB水平增强了ID的敏感性。本文适用模糊逻辑来减少代表ID的核心问题之一的误报。 ID是一种复杂的决策过程,通常涉及有关监控系统的巨大因素。一种模糊逻辑评估组件,它表示分布式IDS中的决策代理模型,在分析入侵行为时,基于模糊逻辑的各种因素。与具有模糊逻辑的ID代理协调获得的性能与相应的非模糊型ID代理进行比较。

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