Articles
| Open Access |
DOI: Multi-Cloud Identity Verification Frameworks: AWS/GCP Hybrid Architectures for Real-Time Fraud Mitigation
Bhaskar Chaganti , Provide Author full affiliationAbstract
The exponential rise in global online transactions intensified the complexity and frequency of identity-fraud attacks, necessitating distributed and intelligent verification systems. A hybrid multi-cloud identity verification framework was designed and evaluated by combining Amazon Web Services (AWS) and Google Cloud Platform (GCP). The framework integrated event-driven serverless components, cross-cloud streaming analytics, and machine-learning-based anomaly detection. In controlled experiments spanning 500–5000 requests per second, P95 decision latency was reduced by 28–31% relative to single-cloud baselines (290ms vs. 420/405ms), and the false-positive rate was reduced by 33–38% (2.8% vs. 4.5%/4.2%). Overall detection accuracy reached 96.4% and end-to-end system availability reached 99.9%.
Keywords
Multi-cloud, identity verification, fraud detection, risk score fusion, latency, false positive rate, AWS Cognito, Google Cloud Identity Platform, streaming analytics, anomaly detection, Zero Trust, hybrid architecture, Kafka, serverless
References
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Google Cloud, “Identity platform documentation,” https://cloud.google.com/identityplatform/docs, 2025, accessed: 2025-08-17.
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