基于Spark的随机森林的网络入侵检测方法

随着信息数据传输内容的不断丰富,信息传输方式的多样化,在网络安全管理中,需要改变传统网络安全管理以被动管理为主的模式,强化网络攻击的主动检测能力。基于Spark的随机森林算法在目前的理论研究中,已经取得了较为深入的研究成果,同时由于其在实际运行中所具有的优势,在应用于网络入侵检测中,具有较好的实用效果。本文对这方面的研究进行简要说明,以期为后续研究工作的开展起到应有的支撑作用。

Network intrusion detection method based on Spark random forest

With the continuous enrichment of information data transmission content and the diversification of information transmission methods, in network security management,it is necessary to change the traditional passive security management-based model to strengthen the active detection capability of network attacks. Spark-based random forest algorithm has achieved in-depth research results in the current theoretical research. At the same time, because of its advantages in actual operation, it has a good practical effect in network intrusion detection. This article briefly explains the research in this area, with a view to supporting the development of subsequent research work.