# Trust-Aware Causal Consistency Routing for Quantum Key Distribution Networks Against Malicious Nodes

## TL;DR

This paper introduces a new routing framework for quantum key distribution networks that improves reliability and efficiency in the presence of malicious nodes.

## Contribution

The novel Trust-Aware Causal Consistency Routing framework prevents malicious nodes from disrupting secure key distribution.

## Key findings

- The proposed framework achieves a high demand completion ratio (mean 0.90) with low key utilization (16.6 keys per demand).
- It outperforms existing protocols like Multi-Path Planned and OSPF in adversarial network conditions.

## Abstract

Quantum key distribution (QKD) networks promise information-theoretic security for multiple nodes by leveraging the fundamental laws of quantum mechanics. In practice, QKD networks require dedicated routing protocols to coordinate secure key distribution among distributed nodes. However, most existing routing protocols operate under the assumption that all relay nodes are honest and fully trustworthy, an assumption that may not hold in realistic scenarios. Malicious nodes may tamper with routing updates, causing inconsistent key-state views or divergent routing plans across the network. Such inconsistencies increase routing failure rates and lead to severe wastage of valuable secret keys. To address these challenges, we propose a distributed routing framework that combines two key components: (i) Causal Consistency Key-State Update, which prevents malicious nodes from propagating inconsistent key states and routing plans; and (ii) Trust-Aware Multi-path Flow Optimization, which incorporates trust metrics derived from discrepancies in reported states into the path-selection objective, penalizing suspicious links and filtering fabricated demands. Across 50-node topologies with up to 30% malicious relays and under all three attack modes, our protocol sustains a high demand completion ratio (DCR) (mean 0.90, range 0.81–0.98) while keeping key utilization low (16.6 keys per demand), decisively outperforming the baselines—Multi-Path Planned (DCR 0.48, 30.8 keys per demand) and OSPF (DCR ≤0.12, 296 keys per demand; max 1601). These results highlight that our framework balances reliability and efficiency, providing a practical and resilient foundation for secure QKD networking in adversarial environments.