Application and Performance Optimization of Deep Learning in 5G Network Intrusion Detection System
Abstract
As the core of next-generation information infrastructure, 5G networks with their ultra-high bandwidth, ultra-low latency, and massive connectivity capabilities drive innovation in critical sectors like intelligent transportation systems and industrial internet. However, their
complex architectures and open application scenarios also expose them to heightened security challenges. Intrusion detection systems (IDS),
serving as the first line of defense in network security, must address the increasingly intelligent, covert, and diverse attack methods prevalent
in 5G environments. Traditional rule-based or shallow machine learning detection approaches struggle to meet real-time performance and
accuracy requirements. Deep learning, with its powerful feature extraction and complex pattern recognition capabilities, offers a new technical pathway for building efficient 5G network intrusion detection systems. This paper explores the application mechanisms and performance
optimization strategies of deep learning in 5G intrusion detection, providing significant theoretical and practical value for ensuring secure 5G
network operations and promoting the healthy development of the digital economy.
complex architectures and open application scenarios also expose them to heightened security challenges. Intrusion detection systems (IDS),
serving as the first line of defense in network security, must address the increasingly intelligent, covert, and diverse attack methods prevalent
in 5G environments. Traditional rule-based or shallow machine learning detection approaches struggle to meet real-time performance and
accuracy requirements. Deep learning, with its powerful feature extraction and complex pattern recognition capabilities, offers a new technical pathway for building efficient 5G network intrusion detection systems. This paper explores the application mechanisms and performance
optimization strategies of deep learning in 5G intrusion detection, providing significant theoretical and practical value for ensuring secure 5G
network operations and promoting the healthy development of the digital economy.
Keywords
Deep learning; 5G network; Intrusion detection system
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PDFReferences
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DOI: http://dx.doi.org/10.70711/aitr.v3i2.7858
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