Enhancing Electoral Integrity: A Multi-layered Approach to Electronic Voting Security Using Arduino and Biometric Authentication
No Thumbnail Available
Date
2025-04-13
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
Today’s electronic voting machines are involved in a range of problems related to the increased complexity of procedures, efficient hackers, and misuse of data. In these conditions, the trustworthiness and openness of elections may not be ensured, and the introduction of a secure approach to utilizing electronic voting will be relevant. The paper discusses the Multi-Layered Approach to Electronic Voting Security, which combines biological, cryptographic, and physical elements to enhance reliability and transparency. It emphasizes the importance of biometric and RFID verification, machine learning algorithms, and SHA-256 for voter data privacy and integrity. The proposed method aims to address the challenges of fraud avoidance and maintaining vote integrity and provides a stronger foundation for administering credible and honest elections in future. The study aims to demonstrate the effectiveness of the multi-layered approach in fraud avoidance and maintaining vote integrity, as well as create, plan, and assess the method. In this way, the present issue can be tackled with the proposed method, which would address the present issue by providing a stronger foundation for credible and honest elections. The study demonstrates the effectiveness of the multi-layered approach in fraud avoidance and maintaining vote integrity and includes the creation, planning, and assessment of the method.
Description
This research study is collaborative research between the students and faculty members of AIUB, Dhaka and IIUC, Chittagong, Bangladesh.
Keywords
EVM, Biometrics, KNN, SHA-256, RFID, Electronic Voting Security
Citation
M. T. Chowdhury, S. A. Tanim, T. E. Shrestha, M. F. Hossain, and Muhibul Haque Bhuyan, “Enhancing Electoral Integrity: A Multi-Layered Approach to Electronic Voting Security Using Arduino and Biometric Authentication,” Proceedings of the 5th International Conference on Data Analytics and Management (ICDAM2024), organized by the London Metropolitan University, UK, 14-15 June2024, pp 643-654. Published in Lecture Notes in Networks and Systems, vol 1299. Springer, Singapore on 13 April 2025. DOI: https://doi.org/10.1007/978-981-96-3358-6_47.
