RISK-AWARE CONTINUOUS AUTHENTICATION FOR CLOUD-NATIVE BANKING APPLICATIONS

Abstract

Cloud-native banking applications have transformed digital financial services by enabling scalable, resilient, and highly available banking platforms capable of supporting real-time transactions, mobile banking, digital payments, and financial analytics. However, continuously evolving cyber threats, credential theft, insider attacks, session hijacking, account takeover, API exploitation, and identity compromise present significant security challenges. Conventional authentication mechanisms primarily rely on one-time user verification, making them insufficient for protecting cloud-native financial services against dynamic cyber threats. Recent advances in Continuous Authentication, Machine Learning (ML), behavioral analytics, Zero Trust Architecture (ZTA), cloud security, and risk-aware access control enable adaptive identity verification throughout active user sessions. This paper proposes a Risk-Aware Continuous Authentication framework for cloud-native banking applications by integrating behavioral analytics, intelligent risk assessment, adaptive authentication, Zero Trust principles, cloudnative monitoring, and real-time threat analytics. The proposed framework continuously evaluates user behavior, transaction context, device posture, session characteristics, workload interactions, and threat intelligence before dynamically adjusting authentication requirements. Experimental analysis demonstrates significant improvements in authentication accuracy, fraud prevention, cyberattack detection, operational resilience, regulatory compliance, and enterprise security compared with conventional static authentication approaches. Keywords: Continuous Authentication, CloudNative Banking, Zero Trust Architecture, Behavioral Analytics, Machine Learning, Risk Assessment, Identity Management, Cloud Security, Financial Cybersecurity, Adaptive Authentication.