A Survey on Machine Learning based Intrusion Detection Systems Using Apache Spark

Hao Lin
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Abstract

The emergence and wide application of the Internet have brought convenience to people's lives, but at the same time, it has also brought many security problems. How to protect network security and prevent intrusion detection is the focus of current research. This article adopts the method of review, first introduces the application examples of big data technology and machine learning technology in intrusion detection respectively, and then introduces intrusion detection system, machine learning algorithm and deep learning algorithm in detail. Finally, the model of spark applied to intrusion detection system is listed, and it is concluded that the combination of spark and machine learning technology for intrusion detection system can make it more efficient.
基于机器学习的Apache Spark入侵检测系统研究
互联网的出现和广泛应用,给人们的生活带来了便利的同时,也带来了许多安全问题。如何保护网络安全,防止入侵检测是当前研究的热点。本文采用综述的方法,首先分别介绍了大数据技术和机器学习技术在入侵检测中的应用实例,然后详细介绍了入侵检测系统、机器学习算法和深度学习算法。最后,给出了应用于入侵检测系统的spark模型,并得出了将spark与机器学习技术相结合用于入侵检测系统可以提高系统效率的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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