基于协同架构的入侵预测系统

E. Pontes, A. Guelfi
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引用次数: 9

摘要

入侵检测系统(IDS)的常用方法缺乏安全性,因为它们是事后处理的方法:只有在不需要的互联网流量(UIT)造成严重损害后才检测和/或阻止它。尽管在过去几年中已经应用了一些预报技术来改进IDS,但这些技术存在三个主要差距:传感器的使用、只使用一种预报技术和预报的共享。本文的目的是展示一个具有预测方法的IDS协作架构,覆盖当前预测技术的空白。提出了这种体系结构的概念证明,从而可以得出关于IDS预测的改进以应对UIT的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IFS — Intrusion forecasting system based on collaborative architecture
Common methods for Intrusion Detection Systems (IDS) lack in security as they are postmortem approaches: Unwanted Internet Traffic (UIT) is detected and/or blocked only after UIT has inflicted serious damage. Even though some forecasting techniques have been applied to improve IDS in the last few years, three major gaps lie in those techniques: sensors employment, the use of just one forecasting technique and forecasts' sharing. The aim of this paper is to show a collaborative architecture of IDS with prediction approaches, covering the gaps of the current forecasting techniques. A proof of concept of such architecture is presented, which allows concluding about the improvement in forecasts for IDS to cope with UIT.
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