AI-Augmented Quantum Key Distribution for Resilient Cloud Data Security: An Integrated Framework for Threat-Adaptive Key Management

Abstract

Cloud computing infrastructure faces a converging threat from classical adversaries exploiting software and channel vulnerabilities and quantum-capable adversaries that render RSA and ECC public-key cryptography asymptotically insecure via Shor's algorithm. Existing Quantum Key Distribution (QKD) implementations detect eavesdropping through Quantum Bit Error Rate (QBER) monitoring but operate reactively and lack autonomous threat classification and cloud-native key management pathways. This paper introduces AI-Augmented Quantum Key Distribution (AI-QKD), a formally specified, cloud-native framework that embeds a two-layer Long Short-Term Memory (LSTM) anomaly engine directly within the QKD key lifecycle to enable proactive, threat-adaptive key refresh.