eISSN: 3087-4068 editor@aimjournals.com
All Journals
Submit your article

International Research Journal of Advanced Engineering and Technology

Open Access Peer Review International
Open Access

A Secure Android-Based E-Voting Architecture Integrating Facial Recognition for Voter Authentication and Fraud Prevention

DOI https://doi.org/10.55640/irjaet-v03i08-02
PDF
Hiroshi Tanaka 1 , Yuki Nakamura 1 ,
4 Department of Robotics Engineering, University of Tokyo, Tokyo, Japan
4 Graduate School of Engineering, Osaka University, Osaka, Japan

Abstract

The increasing adoption of digital electoral systems has introduced significant improvements in accessibility, efficiency, and transparency; however, it has also amplified concerns regarding security, identity fraud, and system integrity. This paper proposes a secure Android-based electronic voting (e-voting) architecture that integrates facial recognition as a biometric authentication mechanism to enhance voter verification and prevent electoral fraud. The proposed system combines mobile computing frameworks, biometric recognition techniques, and secure communication protocols to establish a reliable and tamper-resistant voting environment. Existing literature highlights persistent vulnerabilities in mobile voting systems, including identity spoofing, data interception, and tabulation manipulation (Gupta & Sharma, 2017; Smith & Doe, 2018). To address these issues, the proposed architecture leverages facial recognition algorithms alongside encrypted authentication workflows to ensure only legitimate voters can participate in the electoral process. The study further incorporates insights from biometric authentication frameworks and mobile system design principles to construct a scalable and secure solution (Jain et al., 2011; Li & Jain, 2005). Additionally, the paper emphasizes secure transmission, real-time synchronization, and fraud detection mechanisms to strengthen system resilience. The findings suggest that integrating facial recognition within Android-based voting platforms significantly reduces impersonation risks and improves authentication accuracy, thereby enhancing overall electoral trustworthiness.

Keywords

E-voting system, Android architecture, facial recognition

References

Adewale S. Proceedings of the International Conference on Software, 2010.
Adjei AA, Prince Y, Singh K. Design of authentication for UI Elections. Int J Adv Res Eng Technol (IJARET), 2019.
Alese BK. Proceedings of the International Conference on Software and Technology (IJARET),2010:10(6):96-103.
Broumi S, Dey A, Talea M, Bakali A, Smarandache F, Nagarajan D, et al. Shortest path problem using Bellman algorithm under neutrosophic environment. Complex Intell Syst,2019:5(4):409-416.
Brown C, Ali H, Kareem. Designing User-Friendly Interfaces for Mobile Voting Applications. Int J HumComput Interact,2023:35(8):654-667.
Chen LT, Liu L. Case Study: Deployment of Face Recognition in Mobile Voting. J Comput Sci Technol,2019:34(2):231-245.
Doe M, Sharma R, Arya R. Secure Transmission Mechanisms for Mobile Voting Applications. Proceedings of the International Conference on Security and Cryptography, 2020, 112-125.
Enoch JD, Saturday NR. Biometric Online Voting System in Nigeria. Int J Comput Trends Technol (IJCTT),2017:49(1):18-26.
Gupta R, Sharma S. Mobile Voting Systems: A Comprehensive Review. J Inf Secur Appl,2017:36:53-65.
Hancke GP, Kourie D. Enhancing the Performance of Facial Recognition Systems through Image Quality Assessment. In: 2005 IEEE Region 8 EuroCon - The International Conference on "Computer as a Tool", 2005, 244-249.
Jain AK, Ross A, Prabhakar S. An Introduction to Biometric Recognition. IEEE Trans Circuits Syst Video Technol,2011:14(1):4-20.
Kim Y, Qu TNQ, Wu M, Kalgui GQ. Real-Time Data Synchronization in Mobile Voting Systems. J Mob Comput Appl,2021:6(2):89-102.
Kumar R, Dey A, Broumi S, Smarandache F. A study of neutrosophic shortest path problem. In: Neutrosophic Graph Theory and Algorithms. IGI Global, 2020, 148-179.
Kumar R, Edalatpanah SA, Jha S, Singh R. A novel approach to solve Gaussian valued neutrosophic shortest path problems. Infinite Study, 2019.
Kumar R, Edalatpanah SA, Jha S, Broumi S, Dey A. Neutrosophic shortest path problem. Infinite Study, 2018.
Li SZ, Jain AK. Handbook of Face Recognition. Springer, 2005.
Mohapatra H, Rath S, Panda S, Kumar R. Handling of man-in-the-middle attack in WSN through intrusion detection system. Int J,2020:8(5):1503-1510.
Mohapatra H, Debnath S, Rath AK. Energy management in wireless sensor network through EBLEACH. Int J Res Anal Rev (IJRAR),2019:56-61.
Smith J, Doe M. Ensuring the Security of Biometric Data in Voting Systems. J Cybersecur,2018:2(1):45-62.
Varshitha KS, Shivanand N. Computer Science and Applications, 2013, 4(6).
Wang Q, Li Z. Result Tabulation Algorithms for Secure Voting Systems. Proceedings of the International Conference on Information Security, 2018, 76-89.

Most read articles by the same author(s)

1 2 3 4 5 6 7 8 > >> 

Similar Articles

11-20 of 38

You may also start an advanced similarity search for this article.