入侵检测系统的递归特征消除算法

H. Nguyen
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引用次数: 0

摘要

计算机网络攻击的识别在安全研究中具有重要意义。本文研究了一套用于入侵检测系统设计的机器学习算法。该入侵检测系统采用递归特征消去法对输入特征进行排序,并根据特征的重要程度生成不同的特征组合,提高了系统的检测性能。交叉验证过程也用于使用大量特征组合的验证数据集上的机器学习技术。该算法对入侵检测系统具有较高的分类性能,在计算机网络的实际环境中具有较好的应用能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recursive Feature Elimination Algorithm for Intrusion Detection Systems
Identification of the attacks on computer networks has significant importance in security research. In this paper, a set of machine learning algorithms are investigated for the design of intrusion detection systems. The detection performance of the proposed intrusion detection system is improved by the application of the recursive feature elimination method to rank the entire input features and generate various feature combinations based on their importance. The crossvalidation procedure is also implemented for the machine learning techniques on the validation dataset using a larger number of feature combinations. The high classification performance of the proposed algorithm for the intrusion detection system implies a better capability of application in the practical environment of computer networks.
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