AI-Driven Threat Detection for UPI and ONDC Platforms: An Empirical Study of Cybersecurity Risks, Trust, and Digital Payment Resilience in India

Abstract

This empirical research article examines cybersecurity risks in India’s Unified Payments Interface (UPI) and the Open Network for Digital Commerce (ONDC), focusing on user-behavior vulnerabilities, platform-level risks, and artificial intelligence’s role in threat detection. UPI’s rapid expansion has increased exposure to phishing, malicious links, identity compromise, malware, and social-engineering frauds. ONDC’s open-network design introduces additional trust, privacy, and security challenges due to multi-participant data exchange. The study uses mixed empirical methods-structured surveys and secondary literature-to assess risk perception, digital-payment trust, cybersecurity awareness, and AI-driven fraud monitoring acceptance. Findings indicate behavioral gaps remain primary vulnerabilities, while AI-driven anomaly detection, continuous authentication, and real-time risk scoring significantly improve fraud prevention and user confidence. The study concludes that cybersecurity in open digital commerce requires technical controls, platform governance, and user education to sustain fintech ecosystem trust.