A secure and scalable framework for post-quantum key management in cloud-based cryptographic systems

Abstract

The advent of quantum computing poses a critical threat to conventional cryptographic systems, potentially rendering many widely used algorithms obsolete. To address this challenge, this study proposes the quantum adaptive security algorithm for key management systems (QASA-KMS), a hybrid security framework that integrates post-quantum cryptography (PQC), machine learning (ML), and blockchain technologies to provide a resilient and intelligent key management solution. Unlike traditional approaches, QASA-KMS uses a one-class support vector machine (OC-SVM) for entropy validation, simulates quantum attacks to proactively assess key robustness, and employs a smart contract-enabled blockchain for secure, decentralized key registration and auditability. Extensive simulations demonstrate that QASA-KMS outperforms established PQC schemes, including Kyber, Dilithium, and nth degree truncated polynomial ring units (NTRU), across key performance metrics such as Shannon entropy, quantum resistance score (QRS), execution latency, and estimated time to crack. The proposed framework achieves a QRS of 97 and maintains an estimated time to crack of 10 million years under simulated quantum-attack models. These results demonstrate the framework’s practicality, efficiency, and resilience in post-quantum threat environments. QASA-KMS therefore provides a modular and future-ready approach to secure cloud-based cryptographic key management.