Intelligent Bayesian classifiers in network intrusion detection

被引：0

作者：

Bosin, A ^{[1
]}

Dessì, N ^{[1
]}

Pes, B ^{[1
]}

机构：

[1] Univ Cagliari, Dipartimento Matemat & Informat, I-09124 Cagliari, Italy

来源：

INNOVATIONS IN APPLIED ARTIFICIAL INTELLIGENCE | 2005年 / 3533卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The aim of this paper is to explore the effectiveness of Bayesian classifiers in intrusion detection (ID). Specifically, we provide an experimental study that focuses on comparing the accuracy of different classification models showing that the Bayesian classification approach is reasonably effective and efficient in predicting attacks and in exploiting the knowledge required by a computational intelligent ID process.

引用

页码：445 / 447

页数：3

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