Zero Trust for Multi-RAT IoT: Trust Boundary Management in Heterogeneous Wireless Network Environments

TL;DR

This paper analyzes how Zero Trust Architecture (ZTA) can be sustained in mobile IoT environments, particularly UAVs, when devices continuously switch between heterogeneous RATs (e.g., 5G/4G, LoRaWAN, Meshtastic, OcuSync, MAVLink, BLE, Wi‑Fi, and satellite). It introduces a formal trust boundary framework: a five-component trust state ${\bf s}=(s_{id},s_{dev},s_{ctx},s_{net},s_{pol})$ forming a composite score ${\mathcal T}$ via a weighted sum, paired with temporal decay and a taxonomy of RAT transitions that govern trust survival and recovery costs. The authors define trust portability concepts to move trust evidence across RAT boundaries, discuss parallel RAT operation, and present a worked UAV case study showing significant trust degradation during transitions and the potential 60–80% energy savings from portable trust artefacts. They integrate regulatory Remote ID as a contextual signal and argue for power-aware trust metrics (Trust-per-Watt) to balance verification rigor with energy constraints in resource-limited mobile deployments. Overall, the work provides a conceptual toolkit—trust state modeling, survival functions, portability mechanisms, and a case study—that enables principled, power-aware ZTA across multi-RAT IoT, paving the way for TpW optimization in future standards and platforms.

Abstract

The proliferation of Multi-Radio Access Technology, Internet of Things devices, particularly Unmanned Aerial Vehicles operating across LoRaWAN, 5G/4G cellular, Meshtastic mesh, proprietary protocols such as DJI OcuSync, MAVLink telemetry links, Wi-Fi, and satellite, creates a fundamental and hitherto unexamined challenge for Zero Trust Architecture adoption. Each transition between radio access technologies constitutes a trust boundary crossing: the device exits one network trust domain and enters another, potentially invalidating authentication state, device attestation, and contextual trust signals. Current ZTA frameworks assume relatively stable network environments and do not address the trust implications of frequent, dynamic RAT switching in mobile IoT deployments.

Figures (2)

• Figure 1: Research gap at the intersection of three established research silos. No prior work addresses Zero Trust trust-state management across heterogeneous RAT transitions including proprietary drone protocols.
• Figure 2: Trust score timeline for a 90-minute multi-RAT UAV mission. The data network trust score (solid blue) exhibits a sawtooth pattern with sharp drops at each RAT transition. The OcuSync C2 link (dotted green) operates as an isolated trust domain with slow natural decay. The drone spends approximately 48 minutes (53%) of the mission with data-network trust below $\mathcal{T}_{\min} = 0.6$.

Theorems & Definitions (11)

• Definition 4.1: Trust State
• Definition 4.2: Composite Trust Score
• Definition 4.3: Trust Decay
• Definition 4.4: Transition Taxonomy
• Definition 4.5: Trust Boundary Crossing
• Definition 4.6: Trust Survival Function
• Definition 4.7: Trust Recovery Cost
• Definition 5.1: Trust Portability
• Definition 5.2: Trust Artefact Security Properties
• Definition 5.3: Parallel Trust Composition