Design of Multilayered Biometric Authentication for a Secure Voting System

International Journal of Emerging Research in Science, Engineering, and Management

Vol. 2, Issue 3, pp. 262–267, March 2026

https://doi.org/10.58482/ijersem.v2i3.33

This work is licensed under a Creative Commons Attribution 4.0 International License .

Design of Multilayered Biometric Authentication for a Secure Voting System

R Leelavathi, B Saraswathi, L Venkateswarlu, G Swetha, O Sai Teja, P Sridhar

Department of ECE, Siddartha Institute of Science and Technology, Puttur, India.

Abstract

This paper presents a secure voting system based on multilayered biometric authentication using embedded systems, IoT, and Python integration. The system employs three layers of identity verification—RFID card authentication, fingerprint recognition, and face detection through a USB camera—ensuring a high level of security and eliminating the chances of fraudulent voting. An Arduino Mega2560 serves as the central controller, with an LCD displaying status messages and a buzzer providing alerts when authentication fails. Push-button switches enable user inputs, while a NodeMCU module facilitates IoT-based monitoring for transparency and data storage. Only after successful authentication across all three layers can a voter cast their vote, thereby enhancing the integrity and reliability of the voting process.

Keywords: Biometric Authentication, RFID, Face Recognition, IoT Monitoring, Secure Voting.

📄 Download Full Text PDF

DOI: https://doi.org/10.58482/ijersem.v2i3.33

Open Access • Peer Reviewed Article

References

  1. H. Ozturk, B. Eraslan, and K. Gorur, “Investigation of t-SNE and Dynamic Time Warping Within a Unified Framework for Resting-State and Minor Analysis Visual Task-Related EEG Alpha Frequency in Biometric Authentication: A Detailed Analysis,” Digital Signal Processing, vol. 160, p. 105042, Feb. 2025. https://doi.org/10.1016/j.dsp.2025.105042
  2. A. Liu, Q. An, S. Xie, and Y. Yan, “SQDPoS: A Secure and Practical Semi-Quantum Blockchain System for the Post-Quantum Era,” Computers, vol. 15, no. 4, p. 210, Mar. 2026. https://doi.org/10.3390/computers15040210
  3. W. Salman, V. Yakovlev, and S. Alani, “Analysis of the Traditional Voting System and Transition to the Online Voting System in the Republic of Iraq,” in 2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), Ankara, Turkey, 2021, pp. 1–5. https://doi.org/10.1109/HORA52670.2021.9461387
  4. A. Iftikhar, K. N. Qureshi, F. B. Hussain, M. Shiraz, and M. Sookhak, “A Blockchain Based Secure Authentication Technique for Ensuring User Privacy in Edge Based Smart City Networks,” Journal of Network and Computer Applications, vol. 233, p. 104052, Nov. 2024. https://doi.org/10.1016/j.jnca.2024.104052
  5. Y. Hmimou, A. Khiat, H. Bensag, Z. Hidila, and M. Tabaa, “Context-Aware Decision Fusion for Multimodal Access Control Under Contradictory Biometric Evidence,” Computers, vol. 15, no. 4, p. 208, Mar. 2026. https://doi.org/10.3390/computers15040208
  6. R. Dang-Awan, J. A. Piscos, and R. B. Chua, “Using Sharemind as a Tool to Develop an Internet Voting System with Secure Multiparty Computation,” in 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA), Zakynthos, Greece, 2018, pp. 1–7. https://doi.org/10.1109/IISA.2018.8633690
  7. A. Rodríguez-Pérez, “Secret Suffrage in Remote Electronic Voting Systems,” in 2017 Fourth International Conference on eDemocracy & eGovernment (ICEDEG), Quito, Ecuador, 2017, pp. 277–278. https://doi.org/10.1109/ICEDEG.2017.7962550
  8. H. Yang, “Adaptive Clustering and Machine-Learning-Based DoS Intrusion Detection in MANETs,” Applied Sciences, vol. 16, no. 6, p. 2723, Mar. 2026. https://doi.org/10.3390/app16062723
  9. S. Wang, X. Xie, T. Wang, and J. Ma, “Attribute-Based Encryption and zk-SNARK Authentication Scheme for Healthcare Systems,” Journal of Information Security and Applications, vol. 94, p. 104241, Sep. 2025. https://doi.org/10.1016/j.jisa.2025.104241
  10. A.-A. Pham, C. T. Nguyen, and T. C. Lam, “Blockchain Adoption for Authentication: A Survey,” Blockchain: Research and Applications, p. 100383, Sep. 2025. https://doi.org/10.1016/j.bcra.2025.100383
  11. C. J. Lakshmi and S. Kalpana, “Secured and Transparent Voting System Using Biometrics,” in 2018 2nd International Conference on Inventive Systems and Control (ICISC), Coimbatore, India, 2018, pp. 343–350. https://doi.org/10.1109/ICISC.2018.8399092
  12. A. Mystakidis et al., “XAI-Driven Malware Detection from Memory Artifacts: An Alert-Driven AI Framework with TabNet and Ensemble Classification,” AI, vol. 7, no. 2, p. 66, Feb. 2026. https://doi.org/10.3390/ai7020066
Download PDF

This article is part of Volume 2, Issue 3 (March 2026)

2026-03-31