Design of a Snort-Based Hybrid Intrusion Detection System

被引：0
|
作者：
Gomez, J. [1 ]
Gil, C. [2 ]
Padilla, N. [1 ]
Banos, R. [2 ]
Jimenez, C. [1 ]
机构：
[1] Univ Almeria, Dept Lenguajes & Computac, Carretera Sacramento S-N, Almeria, Spain
[2] Univ Almeria, Dept Arquitectura Computadores & Elect, Almeria 04120, Spain
来源：
DISTRIBUTED COMPUTING, ARTIFICIAL INTELLIGENCE, BIOINFORMATICS, SOFT COMPUTING, AND AMBIENT ASSISTED LIVING, PT II, PROCEEDINGS | 2009年 / 5518卷
关键词：
Intrusion detection systems; anomaly detection; Network IDS; Snort;
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：
Computer security has become a major problem in our society. In particular, computer network security is concerned with preventing the intrusion of an unauthorized person into a network of computers. An intrusion detection system (IDS) is a tool to monitor the network traffic and users' activity with the aim of distinguishing between hostile and non-hostile traffic. Snort is an IDS available under GPL, which allows pattern search. This paper presents a new anomaly pre-processor that extends the functionality of Snort IDS, making it a hybrid IDS.
引用
收藏
页码：515 / +
页数：3
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