AI-Empowered Neural Security Framework for Protected Financial Transactions in Distributed Cloud Banking Ecosystems
DOI:
https://doi.org/0.15662/IJARCST.2023.0602004Keywords:
AI-enabled encryption, neural network security, distributed cloud banking, financial data protection, anomaly detection, neural cryptography, transaction securityAbstract
The rapid expansion of distributed cloud banking ecosystems has intensified the need for advanced security mechanisms capable of protecting sensitive financial transactions against emerging cyber threats. This paper presents an AI-empowered neural security framework that integrates deep learning–based encryption, anomaly detection, and adaptive threat monitoring to ensure end-to-end protection of financial data across multi-node cloud environments. The proposed architecture leverages neural cryptographic models to dynamically generate secure keys, detect malicious transaction patterns in real time, and autonomously respond to vulnerabilities with minimal human intervention. A hybrid cloud deployment strategy enhances resilience by distributing encrypted transaction loads across multiple secure clusters while maintaining low latency and ensuring compliance with banking security standards. Experimental evaluations demonstrate significant improvements in transaction confidentiality, intrusion detection accuracy, and response time compared to traditional cloud security models. The framework establishes a scalable, intelligent, and self-evolving security layer tailored for modern digital banking infrastructures.
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