Towards Realistic Waveform-Level IoT Network Simulation via IQ Mixing

2026-04-09T07:23:56Z50f57833b0d4420fe5125e3b740a4c1914f526ad50b20a74869f4bd8940e120c
5G NRBLEIQ mixingIoTLLMsLoRaWANQKDUAVagentic AIconsensuscontextual authenticationfederated learningintent-based networkinginterference coordinationjammingledgermodel poisoningnetwork securitypartition tolerancephysical-layerquantum communicationsplit learningsynchronization attackstime synchronizationwaveform simulation

What happened

Collection of recent networking and distributed-systems papers with multiple security-relevant implications. Key points: IQSim (IQ-domain waveform mixing) enables realistic PHY-level experiments but also lowers the barrier for developing and testing waveform/physical-layer attacks (adjacent-channel leakage, cross‑modulation, jamming). Integrating agentic LLMs into intent-based networking (IBN) increases attack surface (compromise of intent translation, supply-chain and knowledge-base poisoning, unauthorized actuation), while the proposed multi-agent IBN architectures highlight need for robust,

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_ni
Record identifier
50f57833b0d4420fe5125e3b740a4c1914f526ad50b20a74869f4bd8940e120c
Enrichment time
2026-04-09T07:23:56Z
AI-assisted enrichment
Yes

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