Open AccessResearch on Network Intrusion Detection Method Based on Deep Learning Algorithm
Author(s) -
Xinhai Liao,
Jun Xie
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1982/1/012121
Subject(s) - intrusion detection system , computer security , network security , computer science , field (mathematics) , information security , big data , the internet , artificial intelligence , data mining , world wide web , pure mathematics , mathematics
Information security is very important in enterprises. Under the tide of modern network informationization, especially intrusion detection is facing great challenges. The rise of technologies such as big data and artificial intelligence, on the one hand, helps to strengthen information security, on the other hand, it also brings great challenges to information security. Everything has two sides, and the Internet is no exception. While the network has brought us a richer and faster life, the problem of network security has become increasingly prominent, and network security risks pose new challenges to the fields of politics, economy, culture, national defense, ecology and society. The active defense strategy using intrusion detection technology can actively discover attacks when they occur or attempt to attack, realize real-time response, and provide real-time protection for network systems. This paper starts from the field of intrusion detection and combines deep learning technology to design an efficient and intelligent intrusion detection model which can be used in the field of network intrusion detection.