摘要
文章利用机器学习方法提出了一种智能入侵检测系统。为了对网络数据进行特征表示,提升系统性能,通过特征提取等方法对数据进行处理。文章提出了一种包含6种不同策略的入侵检测模型框架,并使用UNSW-NB15数据集进行了网络入侵检测实验。实验结果表明,该入侵检测模型检测效果优良,易于使用。
In this paper,an intelligent intrusion detection system was proposed.We pay attention to the feature extraction problem which can make the detection model robust and improve the performance.A framework containing six different strategies is adopted.IDS in this paper was demonstrated using UNSW-NB15 dataset.The simulation results were quite satisfactory compared to some existing models.
作者
康健
王杰
李正旭
张光妲
KANG Jian;WANG Jie;LI Zhengxu;ZHANG Guangda(Beijing Institute ofAstronautical Systems Engineering,Beijing 100076,China;College of Information and Communication Engineering,Harbin Engineering University,Harbin Heilongjiang 150001,China;Taiyuan Satellite Launch Centre General Section,Taiyuan Shanxi 030027,China;College of Computer and Control Engineerings Qiqihar University,Qiqihar Heilongjiang 161006,China)
出处
《信息网络安全》
CSCD
北大核心
2019年第9期21-25,共5页
Netinfo Security
基金
国家自然科学基金[61771154]
黑龙江省教育厅科学技术研究项目[12531767]
