Frontiers of Data and Domputing ›› 2021, Vol. 3 ›› Issue (3): 59-74.doi: 10.11871/jfdc.issn.2096-742X.2021.03.006

• Special Issue: Communication and Security of Network • Previous Articles     Next Articles

A Survey on Network Intrusion Detection Based on Deep Learning

XIAO Jianping1,2(),LONG Chun1,2,*(),ZHAO Jing1(),WEI Jinxia1(),HU Anlei3(),DU Guanyao1,2()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China
    2. School of Computer Science and Technology, University of Chinese Academy of Sciences, Beijing 101408, China
    3. China Internet Network Information Center, Beijing 100190, China
  • Received:2021-05-09 Online:2021-06-20 Published:2021-07-09
  • Contact: LONG Chun;;;;


[Objective] The rapid development of the Internet has brought great convenience to people's life. However, various malicious network attacks are also increasing, and cyberspace is facing serious threats. Intrusion detection plays a key role in preventing network attacks. [Coverage] In recent years, deep learning methods have been widely used in the field of intrusion detection. In this paper, through an extensive literature survey, we select the latest research work in this field. [Methods] Firstly, this paper introduces the current network security situation and summarizes the types, data sets, and evaluation methods of intrusion detection systems. In the aspect of detection technology, it discusses traditional machine learning and deep learning methods. Finally, it introduces the future research direction of intrusion detection technology. [Results] Through analysis and comparison, it shows that intrusion detection systems based on deep learning methods usually have better performance.[Limitations] Due to the scope of the available literature, this article does not make a comparison in the view of the problems solved by various intrusion detection methods based on deep learning. [Conclusions] Intrusion detection technologies based on deep learning have advantages in processing high-dimensional data, obtaining hidden information in data, and solving the problem of data imbalance in the network. In the future, it will be more and more widely used in the field of intrusion detection.

Key words: cyber security, intrusion detection, deep learning, machine learning