A Duress-Enabled Mobile Banking System for Coercion-Resistant Transactions

This study addresses the critical security gap in mobile banking systems where victims of physical coercion are forced to authorize financial transactions under threat. A novel duress-enabled banking framework was designed and implemented, incorporating dual-authentication mechanisms, duress PINs, and duress login modes that enable victims to comply with attackers while covertly activating protective measures. The system combines AI-driven anomaly detection, behavioral biometrics, and blockchain-inspired fixed logging through a comprehensive, coercion-resistant architecture. When duress credentials are entered, transactions appear normal to the coercers but trigger backend restrictions that limit transfer amounts, disable cash withdrawals, route funds through traceable interbank channels, embed forensic markers, and issue silent alerts to bank security operations. A prototype was developed and evaluated through scenario-based activities covering robbery situations, potential misuse, and accidental activation. The results show an effective balance between the safety of the victim, recovery of funds, and abuse prevention. The framework uses machine learning algorithms, verification of geolocation, and behavioral analysis to differentiate between genuine duress and fraudulent claims. This research contributes the first systematic technical solution for coercion-based financial crimes, provides implementation guidance for banking institutions, and establishes foundations for regulatory frameworks governing duress-aware transactions, with particular relevance for emerging markets experiencing high rates of coercive financial crimes.