Extracting of temporal patterns from data for hierarchical classifiers construction

M. Szpyrka, A. Szczur, Jan G. Bazan, Lukasz Dydo
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Abstract

A method of automatic extracting of temporal patterns from learning data for constructing hierarchical behavioral patterns based classifiers is considered in the paper. The presented approach can be used to complete the knowledge provided by experts or to discover the knowledge automatically if no expert knowledge is accessible. Formal description of temporal patterns is provided and an algorithm for automatic patterns extraction and evaluation is described. A system for packet-based network traffic anomaly detection is used to illustrate the considered ideas.
从数据中提取时间模式用于分层分类器的构建
本文研究了一种从学习数据中自动提取时间模式的方法,用于构建基于层次行为模式的分类器。所提出的方法可以用于完成专家提供的知识,也可以用于在没有专家知识的情况下自动发现知识。给出了时间模式的形式化描述,并描述了一种自动提取和评估模式的算法。用一个基于分组的网络流量异常检测系统来说明所考虑的思想。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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