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Advanced Quantum-Resilient Frameworks for Anomaly Detection in Multi-Tenant Hybrid Cloud Environments
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 39 |
| Year of Publication: 2025 |
| Authors: Bareq M. Khudhair, Karrar M. Khudhair |
10.5120/ijca2025925680
|
Bareq M. Khudhair, Karrar M. Khudhair . Advanced Quantum-Resilient Frameworks for Anomaly Detection in Multi-Tenant Hybrid Cloud Environments. International Journal of Computer Applications. 187, 39 ( Sep 2025), 30-38. DOI=10.5120/ijca2025925680
Abstract
This research addresses the compounded security risks in multi- tenant hybrid cloud environments arising from advanced cyber threats and the emerging capabilities of quantum computing. The study proposes Q-ZAP, a Quantum-Resilient Zero-Trust Anomaly- detection Platform that integrates Post-Quantum Cryptography (PQC) and a Hybrid Quantum-Classical Machine Learning (QML) model within a Zero-Trust Architecture (ZTA). The core component is a Hybrid Autoencoder (HAE) designed for unsupervised anomaly detection in high-dimensional cloud log data. The system employs NIST-standardized PQC algorithms (ML-KEM and ML-DSA) to secure both control and data planes. Experimental results in a simulated environment demonstrate a 13.3% improvement in F1-score over classical baselines, with acceptable overhead from PQC integration.
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