A Model of Intrusion Detection Based on Data Mining and Neural Network

摘要：

Today, we often apply the intrusion detection to aid the firewall to maintain the network security. But now network intrusion detection have problem of higher false alarm rate, we apply the data warehouse and the data mining in intrusion detection and the technology of network traffic monitoring and analysis. After network data is processed by data mining, we will get the certain data and the uncertain data. Then we process the data by the BP neural network, which based on the genetic algorithm, again. Finally, we propose a new model of intrusion detection based on the data warehouse, the data mining and the BP neural network. The experimental result indicates this model can find effectively many kinds behavior of network intrusion and have higher intelligence and environment accommodation.

关键词： Intrusion Detection Data Mining Data Warehouse BP Neural Network Genetic Algorithm

作者: BeiQi Yunfeng Dong

作者单位: Network Center Shandong Institute of Light Industry Jinan, China Computer Center Shandong Institute of Light Industry Jinan, China

会议类型: 国际会议

会议名称: 2011 International Conference on Communication and Electronics Information(ICCEI 2011)(2011年通信和电子信息国际会议)

会议地点: 海口

会议语种:英文

页码: 226-229

在线出版日期: 2011-02-22（万方平台首次上网日期，不代表论文的发表时间）