基于数据挖掘的入侵检测系统

First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008) Pub Date : 2008-01-23 DOI:10.1109/WKDD.2008.12

Zhan Jiuhua

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引用次数: 15

摘要

分析了最近的入侵检测模型，入侵检测系统(IDS)的发展，并对当前的数据挖掘(DM)技术进行了简要介绍。针对当前入侵检测面临的问题，提出了一种基于数据挖掘的入侵检测框架。进行异常检测的系统可以检测已知和未知的入侵，减少遗漏和误报，提高入侵检测的准确性和速度，具有良好的自适应能力和可扩展性。

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Intrusion Detection System Based on Data Mining

Analyzed recent IDS models, the development of IDS (Intrusion Detection System), and the current and gives a brief introduction to DM (Data Mining) technology. Presented a framework of IDS based on data mining for resolving the current problems IDS is facing. The system that performs anomaly detection can detect intrusions known and unknown, reduce omissions and misstatements, improve accuracy and speed of intrusion detection and has good adaptive capacity and scalability.

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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)

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