StormShield fingerprints and blocks malicious UEs in O-RAN 5G RANs to prevent RRC signaling storms, achieving 97.6% detection accuracy within 106.5 ms on an OTA testbed with OAI and commercial hardware.
An Unsupervised Graph Neural Network Approach to Deceive UAV Network Reconnaissance Attack,
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LatencyScope models 5G RAN latency sources across the protocol stack and provides a configuration analyzer that identifies settings meeting latency-reliability targets, validated on open-source testbeds and commercial network measurements where it outperforms prior models and simulators.
SinFormer is a tailored transformer that applies multi-scale self-attention and staged training to improve accuracy and robustness in radio frequency fingerprint identification on real-world data.
GraphSAGE achieves 94.2% detection rate, 0.955 AUC, and 1.4s response time for cyberattacks on drone systems in an emulation study, outperforming GCN and GAT.
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Graph neural networks at war: integrating cybersecurity and drone intelligence in the Israeli-Iranian conflict
GraphSAGE achieves 94.2% detection rate, 0.955 AUC, and 1.4s response time for cyberattacks on drone systems in an emulation study, outperforming GCN and GAT.