{"ID":3004832,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-05T11:43:53.432517148Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.03611","arxiv_id":"2606.03611","title":"Q-FE: A Quantum-Native 6G Far-Edge Architecture Securing Industrial IoT Digital Twins via CSIDH-PQC and Asynchronous Federated Learning","abstract":"Sixth-generation (6G) wireless networks will underpin ultra-dense Industrial IoT (IIoT) ecosystems in which resource-constrained Far-Edge devices -- autonomous mobile robots, industrial actuators, connected vehicles -- must simultaneously satisfy sub-millisecond latency, $10^{-7}$-class reliability, and decades-long cryptographic security. Current architectures delegate Digital Twin (DT) computation to centralised cloud or Mobile Edge Computing (MEC) servers, incurring prohibitive round-trip latency, and rely on classical public-key cryptography vulnerable to quantum attacks under the harvest-now, decrypt-later (HNDL) threat model. We propose Q-FE, a Quantum-Native 6G Far-Edge architecture integrating three co-designed components: (i) Micro-Digital Twins ($μ$DTs) co-located with 6G base stations and high-capability endpoints; (ii) a Cross-Layer Post-Quantum Key Exchange module embedding CSIDH-512 isogeny key material directly within MAC-layer control frames, exploiting the scheme's uniquely compact keys ($\\le 64$ bytes) to avoid packet fragmentation; and (iii) an Asynchronous Federated Learning (AFL) protocol governed by lightweight DAG smart contracts at MEC nodes, eliminating straggler bottlenecks and preventing model-poisoning and Sybil attacks without exposing raw data. End-to-end simulations (NS-3 + PySyft) demonstrate that Q-FE reduces MAC-layer overhead by 62% versus ML-KEM/Kyber-1024, maintains P99.9 URLLC latency at 0.78 ms, and accelerates global-model convergence by 31% over synchronous Federated Learning. Protocol complexity analysis confirms $O(N \\log R)$ per aggregation round, and $μ$DT handover migration completes in $1.9 \\pm 0.3$ ms across $10^4$ simulated events. A formal threat model confirms resilience against quantum eavesdropping, model-poisoning, and Sybil attacks.","short_abstract":"Sixth-generation (6G) wireless networks will underpin ultra-dense Industrial IoT (IIoT) ecosystems in which resource-constrained Far-Edge devices -- autonomous mobile robots, industrial actuators, connected vehicles -- must simultaneously satisfy sub-millisecond latency, $10^{-7}$-class reliability, and decades-long cr...","url_abs":"https://arxiv.org/abs/2606.03611","url_pdf":"https://arxiv.org/pdf/2606.03611v1","authors":"[\"Vincenzo Sammartino\"]","published":"2026-06-02T13:13:44Z","proceeding":"cs.CR","tasks":"[\"cs.CR\",\"cs.ET\"]","methods":"[]","has_code":false}