Detection and Analysis of Intrusion Characteristic Based on BP Neural Network

被引：0
|
作者：
Guo Hongliang [1 ]
Kong Shaoying [2 ]
机构：
[1] JiLin Agr Univ, Changchun 130118, Jilin, Peoples R China
[2] JiLin Radio & Televis Univ, Changchun 130022, Peoples R China
来源：
ADVANCES IN MECHATRONICS, AUTOMATION AND APPLIED INFORMATION TECHNOLOGIES, PTS 1 AND 2 | 2014年 / 846-847卷
关键词：
Computer network intrusion; Characteristic detection; BP neural network;
D O I：
10.4028/www.scientific.net/AMR.846-847.1720
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A Detection and Analysis algorithm base on BP neural network was proposed to solve the problem of low intercept rate, which was exist in traditional algorithm. The traditional algorithm cannot detect the intrusion effectively because the intruder was always combined with other computer virus. The BP neural network can transfer the input to output with nonlinear method, the characteristic was extracted and compare, then the intruder can be detected and intercepted with higher probability. Compared with traditional algorithm, the new algorithm can intercept the intruder with 22% higher rate. Result shows good performance of the algorithm in the intrusion signal detection and excellent perspective in practice.
引用
收藏
页码：1720 / +
页数：2
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