基于机器学习算法的网络入侵检测Network intrusion detection based on machine learning algorithm
张夏
摘要(Abstract)：
网络入侵的频率越来越高,严重危害了网络安全。为了获得高正确率的网络入侵检测结果,针对当前网络入侵检测模型的局限性,提出基于机器学习算法的网络入侵检测模型,通过机器学习算法中性能优异的支持向量机构建"一对一"的网络入侵检测分类器,采用当前标准网络入侵检测数据库对模型的有效性进行验证,网络入侵检测正确率高达95%以上,检测误差远远低于实际应用范围,可以应用于实际的网络安全管理中。
关键词(KeyWords)： 网络安全;入侵行为;机器学习算法;入侵检测;分类器;检测误差
基金项目(Foundation):
作者(Author): 张夏
DOI: 10.16652/j.issn.1004-373x.2018.03.029
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