Secure Wireless Sensor and SDN Integrated Financial Platforms with AI Powered Fraud Detection and Real Time Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2024.0703008Keywords:
Wireless Sensor Networks (WSNs), Software-Defined Networking (SDN), Financial Platforms, AI-powered Fraud Detection, Real-Time Analytics, IoT Security, Network Orchestration, Anomaly Detection, Risk Management, Transaction MonitoringAbstract
The convergence of wireless sensor networks (WSNs) and software-defined networking (SDN) provides a novel framework for secure financial platforms capable of supporting AI-powered fraud detection and real-time analytics. Financial ecosystems increasingly depend on distributed data collection, dynamic network orchestration, and intelligent decision-making to monitor transactions and detect anomalous behavior. Integrating WSNs enables real-time monitoring of IoT-enabled financial devices, point-of-sale systems, and mobile payment terminals, capturing high-resolution data streams. SDN offers programmable network control, dynamic traffic management, and enhanced security policies, allowing financial institutions to enforce fine-grained access control, isolate suspicious network flows, and respond rapidly to potential cyber threats. Coupled with AI-powered analytics, these integrated systems can perform real-time anomaly detection, risk scoring, and adaptive fraud prevention by learning from historical transaction patterns and sensor telemetry. This paper explores the architecture, operational principles, and performance considerations of WSN-SDN integrated financial platforms. It examines the challenges of data reliability, network latency, model deployment, and regulatory compliance while highlighting the advantages of real-time situational awareness, scalable fraud detection, and network-level security. Case studies and simulations demonstrate the potential for reducing financial risk, enhancing operational resilience, and improving customer trust through intelligent, network-aware decision-making frameworks
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