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RAFT: A Real-Time Framework for Root Cause Analysis in 5G and Beyond Vulnerability Detection.

, , , , and . CCNC, page 446-454. IEEE, (2024)

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From Ambiguity to Explicitness: NLP-Assisted 5G Specification Abstraction for Formal Analysis., , , , and . CloudNet, page 229-237. IEEE, (2023)5G RRC Protocol and Stack Vulnerabilities Detection via Listen-and-Learn., , , and . CCNC, page 236-241. IEEE, (2023)Systematic Meets Unintended: Prior Knowledge Adaptive 5G Vulnerability Detection via Multi-Fuzzing., , , and . CoRR, (2023)Toward Auto-Modeling of Formal Verification for NextG Protocols: A Multimodal Cross- and Self-Attention Large Language Model Approach., and . IEEE Access, (2024)HyFuzz: A NextG Hybrid Testing Platform for Multi-step Deep Fuzzing and Performance Assessment from Virtualization to Over-the-Air., and . CloudNet, page 274-280. IEEE, (2023)Formal and Fuzzing Amplification: Targeting Vulnerability Detection in 5G and Beyond., and . CoRR, (2023)Automated Vulnerability Testing and Detection Digital Twin Framework for 5G Systems., , , , , , , and . NetSoft, page 308-310. IEEE, (2023)Formal-Guided Fuzz Testing: Targeting Security Assurance from Specification to Implementation for 5G and Beyond., , and . CoRR, (2023)Towards Auto-Modeling of Formal Verification for NextG Protocols: A Multimodal cross- and self-attention Large Language Model Approach., and . CoRR, (2023)RAFT: A Real-Time Framework for Root Cause Analysis in 5G and Beyond Vulnerability Detection., , , , and . CCNC, page 446-454. IEEE, (2024)