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Falsification Prevention and Protection Technologies and Products

机译:防伪保护技术及产品

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摘要

It becomes increasingly important to detect intrusions with unknown patterns in order to protect our business from cyber terrorism threats. This paper introduces data mining technologies designed for this purpose; SmartSifter (outlier detection engine), ChangeFinder (change-point detection engine), AccessTracer (anomalous behavior detection engine). All of them are able to learn statistical patterns of logs adaptively and to detect intrusions as statistical anomalies relative to the learned patterns. We briefly overview the principles of these engines and illustrate their applications to network intrusion detection, worm detection, and masquerader detection.
机译:为了保护我们的企业免受网络恐怖主义威胁,检测具有未知模式的入侵变得越来越重要。本文介绍了为此目的设计的数据挖掘技术。 SmartSifter(异常检测引擎),ChangeFinder(变更点检测引擎),AccessTracer(异常行为检测引擎)。他们所有人都能够自适应地学习日志的统计模式,并能够将入侵作为相对于所学模式的统计异常进行检测。我们简要概述了这些引擎的原理,并说明了它们在网络入侵检测,蠕虫检测和伪装检测中的应用。

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