An Intrusion Detection Model Based on Deep Belief Network

被引：23
|
作者：
Qu, Feng [1 ]
Zhang, Jitao [1 ]
Shao, Zetian [1 ]
Qi, Shuzhuang [1 ]
机构：
[1] CRRC Qingdao Sifang Co Ltd, Qingdao, Shandong, Peoples R China
来源：
PROCEEDINGS OF 2017 VI INTERNATIONAL CONFERENCE ON NETWORK, COMMUNICATION AND COMPUTING (ICNCC 2017) | 2017年
关键词：
deep learning; intrusion detection; deep belief network;
D O I：
10.1145/3171592.3171598
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The method of network intrusion detection based on deep learning is the hotspot of current research. This paper presents an intrusion detection model based on deep belief network and analyzes the NSL-KDD dataset. The experimental results show that the algorithm improves the detection of abnormal behavior pattern data and satisfies the requirement of high efficiency and reliability of intrusion detection system.
引用
收藏
页码：97 / 101
页数：5
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