Quantum-Safe Fuzzy Transformers for Crossborder Settlement in Decentralized Finance

Abstract

Cross-border payment systems face growing complexity and urgency, driven by rapid globalization, fluctuating exchange rates, and the expansion of decentralized finance (DeFi). Simultaneously, the looming advent of quantum computing threatens to undermine traditional cryptographic methods, pressing the need for future-proof solutions. In this paper, we propose a Quantum-Safe Fuzzy Transformer framework that unifies fuzzy logic with Transformer-based sequence modeling, enhanced by post-quantum cryptographic primitives. Our approach tackles two critical challenges: handling data uncertainty and market volatility-common in cross-border transactions-through fuzzy membership functions seamlessly embedded in the self-attention mechanism, and ensuring robust security against quantum-era threats via lattice-based signatures and key exchanges. Empirical evaluations on a simulated DeFi payment network demonstrate that the proposed model maintains high transaction throughput and low latency, even under stress-test conditions reflecting extreme exchange rate fluctuations. Furthermore, the quantumsafe cryptographic layer defends settlement integrity, highlighting the practicality of post-quantum methods for realworld payment pipelines. By fusing explainable fuzzy transformations with a resilient cryptographic infrastructure, this work paves the way for an AI-driven, trust-minimized ecosystem capable of withstanding the next wave of financial and computational revolutions.