Section Article

An Enhanced and More Secure Automated Teller Machine System
Author(s): Ram Gopal Yadav

Abstract
Automated Teller Machines have become the backbone of modern banking systems providing round-the-clock access to cash and essential banking services for millions of users worldwide. However during the past decade the increase in cyber fraud card skimming PIN theft fake keypads malware-based jackpotting identity duplication and system-level vulnerabilities has created an urgent need for more secure and intelligent ATM infrastructure. Traditional ATM authentication mechanisms rely primarily on magnetic stripe cards and four-digit PIN entry which are now outdated and susceptible to sophisticated attacks. This study proposes an enhanced and secure ATM system integrating biometric authentication multi-layer encryption artificial intelligence–enabled anomaly detection secure hardware modules and blockchain-based transaction validation. The improved model aims to eliminate identity theft prevent unauthorized access and significantly reduce fraudulent withdrawals by introducing fingerprint and facial biometrics encrypted PIN tunneling real-time surveillance analytics tamper-proof components and distributed ledger auditing. The research evaluates existing ATM security loopholes analyses user-centric vulnerabilities and tests a proposed hybrid security framework under simulated conditions. Results indicate a substantial reduction in impersonation card cloning malware injection and skimming-related threats. Furthermore the enhanced system improves transaction transparency user trust operational reliability and network resilience. The proposed model offers a future-ready security architecture suitable for both urban and rural banking environments ensuring safer intelligent and friction-free financial access for all categories of users.