Survey on ATM security enhancement using encryption technology

This paper introduces a novel ATM security system that integrates biometric authentication and advanced encryption techniques to enhance safety. The system employs facial recognition and additional biometric methods to strengthen user identification and prevent fraud. It also includes features like helmet or mask detection and one-time password (OTP) authentication to ensure secure transactions. The security framework leverages technologies such as Convolutional Neural Networks (CNNs) and FaceNet for accurate facial recognition. The proposed ATM design includes two levels of security: biometric authentication using a facial image combined with a 4-digit password. Additionally, encryption is reinforced with a wavelet- based Advanced Encryption Standard (AES) algorithm, providing further protection for sensitive information. Future work may explore refining these methods and incorporating additional layers of security to keep up with evolving threats