Fingerprint and Face Detection with Self Banking Biometric and GSM Technology

The advancement of biometric technology has opened new frontiers in enhancing security measures, particularly in critical systems like Automated Teller Machines (ATMs). This paper presents “Biometric Fortress,” a novel approach utilizing Raspberry Pi-based face and fingerprint recognition systems to bolster the security of ATM operations. By integrating biometric authentication methods, this system aims to mitigate the vulnerabilities associated with traditional PIN-based authentication systems, offering a robust defence against unauthorized access, card skimming, and identity theft. Leveraging the affordability and versatility of Raspberry Pi, the proposed solution provides a cost-effective and scalable framework adaptable to diverse ATM infrastructures. Through a combination of facial recognition and fingerprint scanning, users can securely access ATM services, ensuring a seamless yet highly secure transaction experience. Furthermore, the implementation of this biometric solution not only enhances security but also enhances user convenience, eliminating the need for physical cards or memorized PINs. The Biometric Fortress represents a significant stride towards fortifying ATM systems against evolving security threats, promising a safer and more reliable future for banking transactions worldwide.

Authors

Publication Details

Published
2024-08-23
DOI
https://doi.org/10.1109/acet61898.2024.10730646
Citations
2
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fingerprint and Face Detection with Self Banking Biometric and GSM Technology

R. Ramalakshmi, B.Akshiya Rajasri, B.R.Gunaksha
2 citations
Biometric Identification and Security
0.70
article

Fingerprint and Face Detection with Self Banking Biometric and GSM Technology

R. Ramalakshmi, B.Akshiya Rajasri, B.R.Gunaksha
article en
2 citations

Abstract

The advancement of biometric technology has opened new frontiers in enhancing security measures, particularly in critical systems like Automated Teller Machines (ATMs). This paper presents “Biometric Fortress,” a novel approach utilizing Raspberry Pi-based face and fingerprint recognition systems to bolster the security of ATM operations. By integrating biometric authentication methods, this system aims to mitigate the vulnerabilities associated with traditional PIN-based authentication systems, offering a robust defence against unauthorized access, card skimming, and identity theft. Leveraging the affordability and versatility of Raspberry Pi, the proposed solution provides a cost-effective and scalable framework adaptable to diverse ATM infrastructures. Through a combination of facial recognition and fingerprint scanning, users can securely access ATM services, ensuring a seamless yet highly secure transaction experience. Furthermore, the implementation of this biometric solution not only enhances security but also enhances user convenience, eliminating the need for physical cards or memorized PINs. The Biometric Fortress represents a significant stride towards fortifying ATM systems against evolving security threats, promising a safer and more reliable future for banking transactions worldwide.

Decent work and economic growth
Openalex Percentile: Top 30%
Biometric Identification and Security
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.