A Hybrid Quantum-Driven Framework for Secure Cloud Computing using QNN, ZKE, and Block Chain

Abstract

This research presents a unified and intelligent security framework for cloud computing environments by integrating Quantum Neural Networks (QNNs), Zero-Knowledge Proof Engines (ZKEs), and Blockchain technology. As the scale and complexity of cloud infrastructures grow, traditional security mechanisms are proving insufficient against advanced cyber threats such as Distributed Denial of Service (DDoS), malware attacks, and Man-in-the-Middle (MITM) exploits. The proposed framework leverages the computational power of quantum systems to enhance the performance of Deep Learning models, enabling faster and more accurate threat detection. ZKEs provide privacy-preserving authentication by verifying user identities without revealing sensitive information, while Block chain ensures data integrity, decentralization, and tamper-proof transaction records. Experimental evaluationconducted using IBM Qiskit and a honey net-integrated Deep Neural Network (DNN) demonstrates a significant improvement in detection accuracy, reduced response time, and enhanced system resilience compared to conventional approaches. The results validate the effectiveness of the multi-layered model in addressing real-world cloud security challenges. This research contributes a scalable, privacy-centric, and quantum-secure architectural foundation for the next generation of cloud-based systems