Fuzzy Particle Swarm Optimization for Intrusion Detection

被引：0
|
作者：
Boughaci, Dalila [1 ]
Kadi, Mohamed Djamel Eddine [1 ]
Kada, Meriem [1 ]
机构：
[1] USTHB, FEI, Dept Comp Sci, Lab Artificial Intelligence LRIA, Beb Ezzouar 16111, Alger, Algeria
来源：
NEURAL INFORMATION PROCESSING, ICONIP 2012, PT V | 2012年 / 7667卷
关键词：
Particle swarm optimization; genetic algorithm; fuzzy logic; classification; intrusion detection; DARPA dataset;
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：
This paper tries to propose a fuzzy particle optimization algorithm (FPSO) for intrusion detection. The proposed FPSO classifier works on a knowledge base modelled as a fuzzy rule if-then and improved by a PSO algorithm. The objective is to obtain good quality solutions by optimizing the fuzzy rules generation. The method is tested on the benchmark KDD' 99 intrusion dataset and compared with the fuzzy genetic algorithm and with other existing techniques available in the literature. The obtained results show the efficiency of the proposed approach.
引用
收藏
页码：541 / 548
页数：8
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