Open AccessResearch on Model-based Abnormal Traffic Detection Method
Author(s) -
Jiaxin Han,
Xiaowei Wang
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 - 10.1088/1742-6596/2024/1/012065
Subject(s) - anomaly detection , hotspot (geology) , computer science , anomaly (physics) , data mining , artificial intelligence , geology , seismology , physics , condensed matter physics
Information security has become a concern of all walks of life, and anomaly detection can protect information security, so anomaly detection has become a research hotspot. In this paper, the principles of four commonly used model-based anomaly detection methods, namely, depth-based, distance-based, density-based and deep learning-based detection methods are introduced and their research status is reviewed. Analyzed the characteristics of the four methods, and finally pointed out the future development trend of anomaly detection methods and gave a conclusion.