Enhancing Voting Security and Efficiency

An Electronic Voting Machine (EVM) System Integrated With Biometric Identifiers

Authors

DOI:

https://doi.org/10.57159/gadl.jcmm.2.3.23065

Keywords:

Electronic Voting Machines, Biometric Identifiers, Voting Security, Facial Recognition, Fingerprint Authentication

Abstract

This study explores developing and implementing a novel Electronic Voting Machine (EVM) system integrated with biometric identifiers to enhance voting security and efficiency significantly. Traditionally, voting processes relied on paper ballots, a system fraught with several challenges, including over-voting, the loss or misplacement of ballot papers, environmental harm due to paper consumption, and a lengthy result compilation process. An advanced EVM system is proposed to address these issues, leveraging unique biometric identifiers - facial recognition and fingerprints - for voter authentication and secure vote recording. Our EVM system effectively improves the security against bogus voting and vote repetition, which have been significant concerns in previous voting systems. This robust approach to voter authentication minimizes the likelihood of voting fraud, thus contributing to a more reliable and secure voting process. However, the transition to this advanced EVM system is challenging. The study identifies key
implications, including the impact on employment due to automation, potential inaccuracies and biases associated with biometric technologies, and vital privacy concerns surrounding using sensitive biometric data. Despite these challenges, the proposed system provides a substantial foundation for future enhancements. Opportunities for further development include the integration of additional biometric identifiers like iris recognition, refining the accuracy of current biometric technologies, and strengthening data privacy measures.

Author Biography

Nikhil Ranjan, Department of Computer Science Engineering, Galgotia University, Greater Noida, Uttar pradesh, India 201308

Mr. Nikhil Ranjan, an Assistant Professor in the School of Computing Science Engineering at Galgotias University, is a dedicated educator with over seven years of experience in teaching Computer Science. He is distinguished by his commitment to fostering critical thinking and problem-solving skills. His academic credentials include an M.Tech in Cyber Forensics and a PhD in progress. Ranjan is recognized as a proficient cybersecurity expert, holding certifications in Ethical Hacking and Network Security. He was awarded the Best Faculty Award by Poornima University in 2019-20 for his exceptional teaching. A prolific researcher, he has contributed to national and international journals and conferences. His expert-led workshops in Mobile Forensics, Web Security, and Intellectual Property Rights have been instrumental in academia. Specializing in areas like Cyber Forensics, Ethical Hacking, and Network Security, Ranjan continues to impact the realm of Computer Science with his expertise.

References

M. Khosla, “The possibility of modern India,” Global Intellectual History, 2021.

A. Shah, “What if We Selected our Leaders by Lottery? Democracy by Sortition, Liberal Elections and Communist Revolutionaries,” Development and Change, vol. 52, no. 4, pp. 687–728, 2021.

A. Kud, “Decentralized Information Platforms in Public Governance: Reconstruction of the Modern Democracy or Comfort Blinding?,” International Journal of Public Administration, vol. 46, no. 3, pp. 195–221, 2023.

D. Pawade, A. Sakhapara, A. Badgujar, D. Adepu, and M. Andrade, “Secure Online Voting System Using Biometric and Blockchain,” Advances in Intelligent Systems and Computing, vol. 1042, pp. 93–110, 2020.

T. M. A. Elven and S. A. Al-Muqorrobin, “Consolidating Indonesia’s Fragile Elections Through E-Voting: Lessons Learned from India and the Philippines,” Indonesian Comparative Law Review, vol. 3, no. 1, pp. 63–80, 2021.

S. Agarwal, A. Haider, A. Jamwal, P. Dev, and R. Chandel, “Biometric based secured remote electronic voting system,” 2020 7th International Conference on Smart Structures and Systems, ICSSS 2020, 2020.

A. Olumide, B. Olutayo, and S. Adekunle, “A Review of Electronic Voting Systems: Strategy for a Novel,” International Journal of Information Engineering and Electronic Business, vol. 12, no. 1, pp. 19–29, 2020.

A. K. Tyagi, T. F. Fernandez, and S. U. Aswathy, “Blockchain and Aadhaar based Electronic Voting System,” Proceedings of the 4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020, pp. 498–504, 2020.

A. Shankar, P. Pandiaraja, K. Sumathi, T. Stephan, and P. Sharma, “Privacy preserving E-voting cloud system based on ID based encryption,” Peer-to-Peer Networking and Applications, vol. 14, pp. 2399–2409, jul 2021.

S. Risnanto, Y. B. A. Rahim, N. S. Herman, and A. Abdurrohman, “E-Voting readiness mapping for general election implementation,” Journal of Theoretical and Applied Information Technology, vol. 98, no. 20, pp. 3280–3290, 2020.

Z. Desai and A. Lee, “Technology and protest: the political effects of electronic voting in India,” Political Science Research and Methods, vol. 9, pp. 398–413, apr 2021.

Y. B. Hamdan and A. Sathesh, “Construction of Efficient Smart Voting Machine with Liveness Detection Module,” Journal of Innovative Image Processing, vol. 3, no. 3, pp. 255–268, 2021.

A. C. Sheela and G. F. Ramya, “E-voting system using homomorphic encryption technique,” Journal of Physics: Conference Series, vol. 1770, no. 1, 2021.

I. Arora, “Election Commission of India: Institutionalising Democratic Uncertainties,” Asian Affairs, vol. 52, no. 1, pp. 228–230, 2021.

K. A. Alnajjar and O. Hegy, “Attendance System Based on Biometrics and RFID,” in 2019 Fifth International Conference on Image Information Processing (ICIIP), vol. 2019-Novem, pp. 596–599, IEEE, nov 2019.

S. Jabin, S. Ahmad, S. Mishra, and F. J. Zareen, “iSignDB: A database for smartphone signature biometrics,” Data in Brief, vol. 33, p. 106597, dec 2020.

J. Mason, R. Dave, P. Chatterjee, I. Graham-Allen, A. Esterline, and K. Roy, “An Investigation of Biometric Authentication in the Healthcare Environment,” Array, vol. 8, p. 100042, dec 2020.

S. M. J. Amali, M. D. C., and R. G., “Evolution of Deep Learning for Biometric Identification and Recognition,” in Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era, pp. 147–160, oct 2022.

S. Dargan and M. Kumar, “A comprehensive survey on the biometric recognition systems ased on physiological and behavioral modalities,” Expert Systems with Applications, vol. 143, p. 113114, apr 2020.

M. A. Bhimrao and B. Gupta, “An empirical study of dermatoglyphics fingerprint pattern classification for human behavior analysis,” Social Network Analysis and Mining, vol. 13, p. 79, apr 2023.

J. K. Appati, P. K. Nartey, E. Owusu, and I. W. Denwar, “Implementation of a Transform-Minutiae Fusion-Based Model for Fingerprint Recognition,” International Journal of Mathematics and Mathematical Sciences, vol. 2021, pp. 1–12, mar 2021.

N. Kaushal and P. Kaushal, “Human Identification and Fingerprints: A Review,” Journal of Biometrics and Biostatistics, vol. 02, no. 04, 2011.

R. S. Ghiass, O. Arandjelovic, H. Bendada, and X. Maldague, “Infrared face recognition: A literature review,” in The 2013 International Joint Conference on Neural Networks (IJCNN), pp. 1–10, IEEE, aug 2013.

Y. Kortli, M. Jridi, A. Al Falou, and M. Atri, “Face Recognition Systems: A Survey,” Sensors, vol. 20, p. 342, jan 2020.

Downloads

Published

31-08-2023

How to Cite

Ranjan, N. (2023). Enhancing Voting Security and Efficiency: An Electronic Voting Machine (EVM) System Integrated With Biometric Identifiers. Journal of Computers, Mechanical and Management, 2(3), 9–15. https://doi.org/10.57159/gadl.jcmm.2.3.23065

Issue

Section

Original Articles

Categories

Received 2023-07-06
Accepted 2023-07-29
Published 2023-08-31