Research on Intrusion Detection Based on Incremental GHSOM Neural Network Model

摘要：

　　Compared with the traditional network intrusion detection method that uses the off-line method to train the intrusion detection model on the existing attack samples, even if the detection rate of the existing sample types is high, it is not effective for the new types of attack samples appearing in the network. Identification, such intrusion methods have problems such as slow speed and high cost of updating models, which is not conducive to detecting new types in the network1. This paper mainly focuses on the GHSOM neural network model and explores its incremental intrusion method.

关键词： Incremental Intrusion Detection

作者: Xiaoman Chi Ximin Liu

作者单位: Jilin Communications Polytecnic, Changchun, Jilin, 130012, China

会议类型: 国际会议

会议名称: 2019 6th International Conference on Machinery, Mechanics, Materials and Computer Engineering (MMMCE 2019)(2019 第六届机械、材料和计算机工程国际会议)

会议地点: 呼和浩特

会议语种:英文

页码: 407-410

在线出版日期: 2019-07-27（万方平台首次上网日期，不代表论文的发表时间）