Research on Zero-Trust Cloud Security Protection System Integrating Quantum Encryption and AI Analysis
Department of Mathematics and Computer Science, Adelphi University, New York 11530,
| Abstract: | This paper presents a novel cloud security protection system that integrates quantum encryption, AI behavior analysis, and the Zero Trust Architecture (ZTA) in response to the increasingly severe security risks in the cloud environment. Based on the analysis of 37 typical cloud security incidents worldwide from 2020 to 2024, the research reveals three major weaknesses in the current protection system: the vulnerability of traditional encryption algorithms against quantum computing, the sharp expansion of the attack surface caused by multi-cloud environments, and the security gaps triggered by human factors. To tackle these challenges, this study proposes the following core solutions: 1) Quantum encryption optimization: Replace traditional encryption with lattice-based encryption algorithms (such as Kyber). While effectively fending off quantum computing threats, it achieves a 40% increase in key generation speed and a 15% reduction in TLS handshake time. 2) Intelligent threat detection: Construct a multi-modal deep learning model integrating Convolutional Neural Network (CNN), Long Short-Term Memory Network (LSTM), and Graph Neural Network (GNN) for multi-dimensional analysis of network traffic, system logs, and user behavior. The attack detection accuracy reaches 96.7%, the false alarm rate is 0.6%, and the interception success rate for Log4j vulnerability attacks is as high as 99.2%. 3) Dynamic permission management: Implement fine-grained dynamic permission adjustment and network micro-segmentation based on the Zero Trust Architecture (ZTA), combined with the real-time risk scoring mechanism of User and Entity Behavior Analytics (UEBA). This significantly shortens the vulnerability response time from 50 hours in the traditional solution to within 1 hour, with an 85% efficiency improvement. This comprehensive protection system has significantly enhanced the data security protection ability and system operation efficiency in the cloud environment, especially suitable for complex multi-cloud scenarios. Looking ahead, it is necessary to further explore the collaborative application of post-quantum cryptography and federated learning technologies to address the more severe privacy protection challenges in the era of quantum computing. |
| Keywords: | Cloud Environment; Security Risks; System Prevention; Quantum Encryption; Artificial Intelligence; Zero Trust |
| DOI: | 10.57237/j.cst.2025.04.001 |
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收稿日期: 2025-04-29
接受日期: 2025-07-11
在线出版日期: 2025-09-09
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