Privacy-Preserving AI-Cloud Architecture for Banking and Building Management Systems with SAP-Driven Network Transparency
DOI:
https://doi.org/10.15680/IJCTECE.2025.0806005Keywords:
Privacy-Preserving AI, Cloud Architecture, Banking Systems, Building Management Systems (BMS), SAP Data Intelligence, Network Transparency, Software-Defined Networking (SDN), Secure Data GovernanceAbstract
This paper presents a Privacy-Preserving AI-Cloud Architecture designed to unify Banking and Building Management Systems (BMS) through SAP-driven network transparency and intelligent data orchestration. The proposed framework leverages Artificial Intelligence (AI), Cloud Computing, and Software-Defined Networking (SDN) to create a secure, interoperable, and adaptive ecosystem for financial and infrastructural data management. Privacy preservation mechanisms are embedded through encrypted cloud channels, access control policies, and federated learning, ensuring compliance with regulatory and institutional data standards. SAP integration enhances operational transparency, enabling seamless data visualization, workflow automation, and predictive decision-making. Furthermore, the framework facilitates cross-domain interoperability—linking banking analytics with smart infrastructure monitoring—to optimize performance, resource allocation, and risk assessment. Experimental insights demonstrate improved security posture, transparency, and data-driven efficiency across distributed environments, making the architecture a scalable solution for next-generation digital ecosystems.
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