Application of Machine Learning in Network Intrusion Detection
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    Abstract:

    With the development of network, network security becomes the key course of computer research. Hacker attacks become more and more frequent. The traditional security products have loopholes. Intrusion detection, as an important means of information security, makes up for the shortcomings of the firewall, provides an effective network intrusion detection measures and protects the network security. However, there are a lot of problems in traditional network intrusion detection. Methods based on machine can detect network intrusion automatically, improve the efficiency of intrusion detection, and reduce the false negative rate and false alarm rate. Here, we first introduce some machine learning algorithms briefly, and then analyze the application of machine learning algorithm in network intrusion detection. Moreover ,we compare the advantages and disadvantages of each algorithm applied in intrusion detection. Finally we summarize the application prospect of machine learning to lay the foundation for the network intrusion detection and prevention system with good performance.

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Zhu Kun, Zhang Qi. Application of Machine Learning in Network Intrusion Detection[J].,2017,32(3):479-488.

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  • Received:
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  • Online: June 28,2017
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