Overview of Network Intrusion Detection Technology [网络入侵检测技术综述]

作者：Jian S.; Lu Z.; Du D.; Jiang B.^*; Liu B.

来源：信息安全学报, 2020, 5(4): 96-122.

DOI：10.19363/J.cnki.cn10-1380/tn.2020.07.07

• Cyber security
• Deep learning
• Intrusion detection
• Machine learning
• Reinforcement learning
• Visual analysis

With the development of the Internet era, attacks such as internal threats, zero-day vulnerabilities and DoS attacks are increasing, and network security is becoming more and more important. Intrusion detection has become an important means of network attack detection. With the development of machine learning algorithms, researchers have proposed a large number of intrusion detection techniques. This article reviews these studies. Firstly, it briefly introduces the current network security situation, and gives the application of intrusion detection technology and system in various fields. Then, the existing research work of intrusion detection related technologies and systems is summarized and evaluated from three aspects: data source, detection technology and detection performance. Among them, the detection technology focuses on traditional machine learning, deep learning, reinforcement learning, visual analysis techniques. Finally, the problems in the current research are discussed and the future direction and prospects of the technology are expected. This article hopes to provide some useful thinking for researchers in this field.

• 出版日期2020
• 单位中国科学院大学