Quantum-Resilient Multi-Cloud Encryption Framework for Securing Big Data Using Post-Quantum Lattice-Based Cryptography and Chaotic Slicing

Abstract

Cloud-based data exponential growth and impending quantum computing boost pose a security threat to the traditional cryptographic protocols. Multi-cloud infrastructure, with its redundancy and scalability, imposes sophisticated security risks, particularly against sensitive big data under quantum attack. This work suggests a quantum-resilient encryption framework, QLEF-Sec, that enables secure and robust handling of data in multi-cloud setups. QLEF-Sec combines lattice cryptography with Quantum Key Distribution (QKD) and a new chaotic entropy-based data slicing method to improve data fragmentation, encryption efficiency, and cryptographic security. Two test datasets, IoT Healthcare and Government Geospatial Records, were employed to mimic real-world applications. The system is tested against AES-256, RSA-2048, and conventional lattice schemes at different file sizes over Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP). QLEF-Sec reached 54.9% avalanche effect and an entropy score of 7.05 bits per character, performing better than AES (47.2%, 5.64) and RSA (49.8%, 5.71). It produced the highest encryption throughput (as high as 30.3 MB/s for a 500MB scale) under all conditions. Decryption throughput was also superior to other competing models. QLEF-Sec offers a scalable, quantum-ready, and entropy-augmented security solution for multi-cloud big data infrastructure. Its performance in real time, modularity, and potential compliance with post-quantum standards make it a forward-compatible framework for emerging cybersecurity requirements.