A Two-Stage Anomaly Detection Method Based on User Preference Features and the Deep Fusion Model

A Two-Stage Anomaly Detection Method Based on User Preference Features and the Deep Fusion Model

Rapid and accurate anomaly traffic detection is one of the most important research problems in cyberspace situational awareness. In order to improve the accuracy and efficiency of the detection, a two-stage anomaly detection method based on user preference features and a deep fusion model is propose...

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Bibliographic Details
Main Authors: Sen-Lei Zhang, Bin Zhang, Yi-Tao Zhou, Yue-Xuan Guo, Jing-Lei Tan
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Applied Sciences
Subjects:
two-stage detection
user preference features
deep fusion model
cyberspace situation awareness
Online Access:https://www.mdpi.com/2076-3417/13/10/6217

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