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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM66032

Multi Factor Bio Metric Access Control System For Secure Physical Document Using Fingerprint and Dwelltime Authentication

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM66032

Volume:

10 |

7 |

Jul 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM66032

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

KGR

Kavya G. R

Department of studies in Computer Science (M.Sc.)

Davangere University

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DPG

Dr.Swapna Pavan G

Department of studies in Computer Science (M.Sc.)

Davangere University

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Abstract

Protecting confidential physical documents is essential in organizations and institutions where unauthorized access can lead to information loss and security breaches. This paper presents a Multi-Factor Biometric Access Control System for Physical Documents using an Arduino Uno and a fingerprint sensor for secure authentication. The system verifies the user's fingerprint before actuating a servo motor to unlock the document storage unit. An OLED display provides real-time system status and user guidance, while visual and audible indicators enhance usability and security. The proposed system eliminates the need for traditional keys and passwords, reducing the risk of theft, duplication, and unauthorized access. It is designed to be portable, cost-effective, and energy-efficient for standalone operation. Experimental testing demonstrated reliable authentication, fast response time, and stable lock control. The proposed solution provides a practical and scalable approach for protecting confidential physical documents and can be extended with future security enhancements such as IoT connectivity and remote monitoring.

KEYWORDS

Fingerprint Authentication Biometric Access Control Arduino Uno Document Security Embedded System Servo Motor Access Control System Physical Document Protection.

Cite This Article

Kavya G. R, Dr.Swapna Pavan G, "Multi Factor Bio Metric Access Control System For Secure Physical Document Using Fingerprint and Dwelltime Authentication," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-6, Jul 2026. https://doi.org/10.55041/IJSREM66032

Full Article/Conclusion

This paper presented a Multi-Factor Biometric Access Control System for Physical Documents that provides secure and reliable protection for confidential physical files using fingerprint-based authentication. The proposed system integrates an Arduino Uno, optical fingerprint sensor, servo motor, LCD display, and buzzer to implement an automated document locking mechanism. Experimental results demonstrated that only authorized users could successfully unlock the document locker, while unauthorized access attempts were denied, thereby enhancing the security of physical document storage. The developed prototype is simple, cost-effective, portable, and suitable for applications in educational institutions, offices, banks, and residential environments. The proposed system offers an efficient and practical solution for improving the security of physical document access.

References

[1]    A. K. Jain, K. Nandakumar, and A. Ross, “50 Years of Biometric Research: Accomplishments, Challenges, and Opportunities,” Pattern Recognition Letters, vol. 79, pp. 80–105, 2016 .[2]   I. Velásquez, A. Caro, and A. Rodríguez, “Authentication Schemes and Methods: A Systematic Literature Review,” Information and Software Technology, vol. 94, pp. 30–37, 2018. [3]      P. Arias-Cabarcos, C. Krupitzer, and C. Becker, “A Survey on Adaptive Authentication,” ACM Computing Surveys, vol. 52, no. 4, Article 80, 2019.  [4]     W. Yang, S. Wang, M. Shahzad, and W. Zhou, “A Cancelable Biometric Authentication System Based on Feature-Adaptive Random Projection,” Journal of Information Security and Applications, vol. 58, p. 102704, 2021.  [5]      M. Nappi, S. Ricciardi, and M. Tistarelli, “Context Awareness in Biometric Systems and Methods: State of the Art and Future Scenarios,” Image and Vision Computing, vol. 76, pp. 27–37, 2018. [6]   T. J. Neal and D. L. Woodard, “You Are Not Acting Like Yourself: A Study on Soft Biometric Classification, Person Identification, and Mobile Device Use,” IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 1, no. 2, pp. 109–122, 2019.  [7]     N. Solayappan and S. Latifi, “A Survey of Unimodal Biometric Methods,” in Proceedings of the International Conference on Security and Management, 2006, pp. 57–63. [8]   X. Zhang, L. Yao, C. Huang, T. Gu, Z. Yang, and Y. Liu, “DeepKey: A Multimodal Biometric Authentication System via Deep Decoding Gaits and Brainwaves,” ACM Transactions on Intelligent Systems and Technology, vol. 11, no. 4, Article 49, 2020.  [9]      F. Roli, L. Didaci, and G. L. Marcialis, Adaptive Biometric Systems That Can Improve with Use. London, U.K.: Springer, 2008.  [10]    K. Z. C. Tun and S. M. M. Zaw, “Gait-Based Human Identification Through Intra-Class Variations,” in Proceedings of the 6th International Conference on Inventive Computation Technologies (ICICT), IEEE, 2021, pp. 564–571.

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Publication Date

7/13/2026

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Double-Blind Peer Review

Review Rounds: 2

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