Year: 2024
Type: article
Abstract: This paper studies and proposes a machine learning-based network security framework for cloud computing, which aims to deal with diverse security threats in cloud environments. By designing data collection, feature extraction, model training and dynamic protection mechanisms, the framework can detect and respond to intrusions, malware and abnormal behaviors in the cloud platform in real time. The results show that machine learning has significant advantages in improving detection accuracy and response speed, and the framework has adaptive learning ability and can dynamically adjust protection strategies.
Authors: Yan Li, Genjuan Ma
Institution: Communication University of China, Nanjing
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405073058