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Survey on ATM Security Enhancement using Encryption Technology

Harshita Patil*, Roshani Talmale**, Siddhi Yerpude***, Ruchit Prasad****, Vaibhav Dhudas*****, Harsimran Kaur Vij******, Tejas Ramteke*******

*-******* Computer Science and Engineering, S. B. Jain Institute of Technology, Management and Research, Nagpur, India.

Periodicity:July - December'2024

Abstract

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.

Keywords

Enhancement, Biometric Authentication, Security. ATM Vulnerabilities, Cybersecurity, Data Protection, Cryptography.

How to Cite this Article?

Patil, H., Talmale, R., Yerpude, S., Prasad, R., Dhudas, V., Vij, H. K., and Ramteke, T. (2024). Survey on ATM Security Enhancement using Encryption Technology. i-manager’s Journal on Digital Forensics & Cyber Security, 2(2), 20-29.

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