Pro-active anomaly detection using metadata-based preview of multi-level token mix-up data augmentation

Abstract

This invention relates to a quantum cloud-based processing system for managing transaction data across multi-application environments with enhanced security, adaptability, and efficiency. The system receives transaction data and metadata, encrypts it using dynamically generated quantum encryption keys, and queries downstream applications to retrieve data structure requirements. It creates a hierarchical map to trace data transformations, tokenizes data into standardized units with encoded metadata, and performs multi-level data augmentation using advanced machine learning techniques. The system ensures seamless integration with applications through a soft commit mechanism, detects and categorizes anomalies, and generates comprehensive discrepancy and anomaly impact reports. Dynamic updating modules adapt to changes in application requirements, while logging and storage modules maintain secure and auditable records of all workflows. This invention addresses the complexities of managing sensitive transaction data, ensuring integrity, compliance, and scalability in diverse, high-volume environments.