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Graph Neural Networks with Multi-Head Attention and SHAP-Based Explainability for Robust, Interpretable, and High-Throughput Intrusion Detection in 5G-Enabled Software Defined Networks 认领 引用
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作者 Sarmad Dheyaa Azeez Muhammad Ilyas Saadaldeen Rashid Ahmed 《Computers, Materials & Continua》 SCIE EI 2026年第6期1637-1665,共29页
The rapid evolution of 5G-enabled Software Defined Networks(SDNs)has transformed modern communication systems by enabling ultra-low latency,massive connectivity,and high throughput.However,the increased complexity of ... The rapid evolution of 5G-enabled Software Defined Networks(SDNs)has transformed modern communication systems by enabling ultra-low latency,massive connectivity,and high throughput.However,the increased complexity of traffic flows and the rise of sophisticated cyber-attacks such as Distributed Denial of Service(DDoS),Botnets,Fake Base Stations,and Zero-Day exploits have made intrusion detection a critical challenge.Traditional Intrusion Detection System(IDS)approaches often suffer from poor gen-eralization,high false positives,and lack of interpretability,making them unsuitable for dynamic 5G environments.This paper presents a novel Graph Neural Network(GNN)with Multi-Head Attention(MHA)and SHAP-based explainability for robust,interpretable,and high-throughput intrusion detection in 5G-SDN.The model is evaluated on the NGIDS-DS and 5G-NIDD datasets,along with a real-time 5G testbed,and achieves a detection accuracy of 98.67%and a detection rate of 99.20%,outperforming baseline IDS models(92.15%accuracy and 89.42%detection rate).Latency is reduced to 24.6 ms compared to 47.3 ms in existing methods,while throughput improves from 7420 flows/sec to 11,384 flows/sec,demonstrating scalability under 5G traffic loads.Furthermore,the integration of SHAP ensures an Interpretability Confidence Score(ICS)of 0.92,providing transparency in decision-making for security-critical applications.The proposed framework significantly enhances detection robustness,reduces overhead,and maintains compliance with 5G Ultra-Reliable Low-Latency Communication(URLLC)performance thresholds,making it a strong candidate for real-world 5G deployments. 展开更多
关键词 5G-SDN explainable AI graph neural networks(GNNs) intrusion detection system(IDS) multi-head attention(MHA) NGIDS-DS SHAP network security
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