{"paper":{"title":"StormShield: Fingerprint-Based Detection and Mitigation of RRC Signaling Storms in O-RAN 5G RANs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"StormShield fingerprints malicious UEs to block RRC signaling storms in O-RAN 5G before gNB resources are exhausted.","cross_cats":["cs.CR"],"primary_cat":"cs.NI","authors_text":"Andrea Lacava, Francesca Cuomo, Leonardo Bonati, Michele Polese, Noemi Giustini, Stefano Maxenti, Tommaso Melodia","submitted_at":"2026-05-13T18:45:50Z","abstract_excerpt":"5G networks provide low-latency, high throughput, and massive connectivity, yet the control plane remains exposed to several security threats. Among the most common and impactful threats are Denial-of-Service (DoS) attacks, with Radio Resource Control (RRC) signaling storms being particularly effective and difficult to mitigate. In this attack, a malicious User Equipment (UE) aims to exhaust Next Generation Node Base (gNB) resources, preventing legitimate UEs from establishing a connection. Existing defenses are typically limited to detection, only evaluated through numerical simulations, and "},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Our experimental evaluation demonstrates that StormShield effectively prevents gNB resource exhaustion, identifying and blocking MUEs with an average detection accuracy of 97.6% within 106.5 ms from the beginning of the attack.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The fingerprinting remains reliable under real-world mobility, varying traffic loads, and different UE implementations beyond the two gNB setups tested in the OTA testbed.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"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.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"StormShield fingerprints malicious UEs to block RRC signaling storms in O-RAN 5G before gNB resources are exhausted.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"b28222391cc7b4221bc250eecb33cd9b1dc1af5963cf7eb4a315e4cbfed4f1c2"},"source":{"id":"2605.14032","kind":"arxiv","version":1},"verdict":{"id":"e7e3a395-f477-4bad-9e29-3757679002a7","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-15T02:34:16.667328Z","strongest_claim":"Our experimental evaluation demonstrates that StormShield effectively prevents gNB resource exhaustion, identifying and blocking MUEs with an average detection accuracy of 97.6% within 106.5 ms from the beginning of the attack.","one_line_summary":"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.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The fingerprinting remains reliable under real-world mobility, varying traffic loads, and different UE implementations beyond the two gNB setups tested in the OTA testbed.","pith_extraction_headline":"StormShield fingerprints malicious UEs to block RRC signaling storms in O-RAN 5G before gNB resources are exhausted."},"references":{"count":22,"sample":[{"doi":"","year":2025,"title":"2025.ETSI TS 138 331 V18.6.0: 5G; NR; Radio Resource Control (RRC); Protocol specification","work_id":"b31456ba-c29d-40b3-ad72-20bab858c4d3","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1109/wcnc57260.2024.10570951","year":2024,"title":"Native Support of AI Applications in 6G Mobile Networks Via an Intelligent User Plane","work_id":"44d39f79-c06d-4864-ace7-bbd28087febf","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2020,"title":"Leonardo Bonati, Michele Polese, Salvatore D’Oro, Stefano Basagni, and Tommaso Melodia. 2020. Open, Programmable, and Virtualized 5G Networks: State-of-the- Art and the Road Ahead.Computer Networks182","work_id":"b11f060c-67ed-4551-ba40-17977f394c80","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":1996,"title":"Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu. 1996. A Density- Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. InProceedings of the Second Internationa","work_id":"6638d902-a08c-465b-bbe8-5598a42bebdc","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"10.1109/infocomwkshps61880.2024.10620824","year":2024,"title":"Ferlinda Feliana, Ting–Wei Hung, Binbin Chen, and Ray–Guang Cheng. 2024. Evaluation of Control/User-Plane Denial-of-Service (DoS) Attack on O-RAN Fronthaul Interface. InIEEE INFOCOM 2024 - IEEE Confer","work_id":"f3df141d-a31a-4be3-a233-deb57e6cb191","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":22,"snapshot_sha256":"47b8d61787602f5f49954f65d80e47ae3b8a0ac9544c150077dbd0918fd06f41","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}