Integration of artificial intelligence in e-voting systems for anomaly detection and prevention of electoral data manipulation

  • Abdurrohman Abdurrohman 
    Universitas Teknologi Bandung
    Indonesia
  • Afiyati Afiyati
    Universitas Mercu Buana
    Indonesia
  • Rasiban Rasiban
    Stikom Cipta Karya Informatika, Jakarta
    Indonesia

Abstract

The increasing adoption of electronic voting (e-voting) systems has improved electoral efficiency and accessibility while simultaneously introducing new challenges related to cybersecurity and electoral data integrity. This study aims to examine the integration of Artificial Intelligence (AI) in e-voting systems for anomaly detection and the prevention of electoral data manipulation. Using a library research approach, data were collected through the analysis of books, scientific journals, research reports, and other relevant academic literature related to Artificial Intelligence, anomaly detection, and electoral data integrity. The findings indicate that AI-based anomaly detection mechanisms can effectively identify unusual patterns, suspicious activities, and potential manipulation attempts within electoral datasets. Furthermore, machine learning algorithms enable continuous monitoring and adaptive threat detection, overcoming several limitations of traditional security approaches. The study concludes that integrating AI into e-voting systems can strengthen electoral data integrity, improve security performance, and enhance public trust in digital electoral processes while supporting transparent, reliable, and accountable democratic governance.

Keywords
  • Artificial intelligence; Anomaly detection; Electoral data integrity
Lisensing Information
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References
  1. ababio, H., & Olatokun, W. (2023). Artificial Intelligence, Social Inclusion, And Representation In General Elections In Lesotho: Challenges, Prospects And A Framework For Implementation. Journal Of Contemporary Society & Education (Jcse), 3(1), 43–63.
  2. Ahmed, I., Jeon, G., & Piccialli, F. (2022). From Artificial Intelligence To Explainable Artificial Intelligence In Industry 4.0: A Survey On What, How, And Where. Ieee Transactions On Industrial Informatics, 18(8), 5031–5042.
  3. Ainur, J., Gulzhan, M., Amandos, T., Venera, R., Bulat, S., Zauresh, Y., & Aizhan, S. (2024). The Impact Of Blockchain And Artificial Intelligence Technologies In Network Security For E-Voting. International Journal Of Electrical And Computer Engineering (Ijece), 14(6), 6723–6733.
  4. Ajao, L. A., Umar, B. U., Ohize, H., Dogo, E. M., Esenogho, E., & Cameron, M. (2025). Blockchain Integration With Multimodal Biometric Authentication System For Secure Smart Verifiable Electronic Voting System. Ieee Access.
  5. Aliyu, A. A., Liu, J., & Gilliard, E. (2024). A Decentralized And Self-Adaptive Intrusion Detection Approach Using Continuous Learning And Blockchain Technology. Journal Of Data Science And Intelligent Systems.
  6. Aniche, C., Yinka-Banjo, C., Ohalete, P., & Misra, S. (2021). Biometric E-Voting System For Cybersecurity. In Artificial Intelligence For Cyber Security: Methods, Issues And Possible Horizons Or Opportunities (Pp. 105–137). Springer.
  7. Battista, D. (2025). From Electronic Voting To Ai: Lessons From The Estonian Case On The Transformation Of Digital Democracy. Em Questão, 31, E-145465.
  8. Chatterjee, R. (2020). Fundamental Concepts Of Artificial Intelligence And Its Applications. Journal Of Mathematical Problems, Equations And Statistics, 1(2), 13–24.
  9. Chigova, L. E., & Hofisi, C. (2025). Democratisation And Emerging Technologies In Africa: Can Ai Deliver Free And Fair Elections?
  10. Ertel, W. (2024). Introduction To Artificial Intelligence. Springer Nature.
  11. Hopgood, A. A. (2021). Intelligent Systems For Engineers And Scientists: A Practical Guide To Artificial Intelligence. Crc Press.
  12. Jafar, U., Ab Aziz, M. J., Shukur, Z., & Adnan Hussain, H. (2024). Secure-Tech Triad Enhancing Electronic Voting System Security Through Integrated Blockchain, Ai, And Iot Technologies. Itm Web Of Conferences, 63, 1011.
  13. Jarrahi, M. H., Lutz, C., & Newlands, G. (2022). Artificial Intelligence, Human Intelligence And Hybrid Intelligence Based On Mutual Augmentation. Big Data & Society, 9(2), 20539517221142824.
  14. Krishnamoorthy, C. S., & Rajeev, S. (2018). Artificial Intelligence And Expert Systems For Engineers. Crc Press.
  15. Kühl, N., Schemmer, M., Goutier, M., & Satzger, G. (2022). Artificial Intelligence And Machine Learning. Electronic Markets, 32(4), 2235–2244.
  16. Lee, R. S. T. (2020). Artificial Intelligence In Daily Life.
  17. Maphephe, J. (2025a). Artificial Intelligence (Ai) And Its Role In Electoral Integrity In The Context Of The 2024. Available At Ssrn 5473305.
  18. Maphephe, J. (2025b). Artificial Intelligence (Ai) And Its Role In Electoral Integrity In The Context Of The 2024 South African General Elections—A Policy Analysis Paper. J Cogn Comput Ext Realities, 1(1), 1–15.
  19. Mccarthy, J. (2022). Artificial Intelligence, Logic, And Formalising Common Sense. Machine Learning And The City: Applications In Architecture And Urban Design, 69–90.
  20. Milea, T. D., & Siminiuc, R. (2025). Algorithmic Auditing In The Age Of Disinformation: An Analysis Of Electoral Integrity Challenges In Eastern Europe. 2025 24th Roedunet Conference: Networking In Education And Research (Roedunet), 1–7.
  21. Mulli, J. (2024). From" Do No Evil" To" Can’t Do Evil" Ai-Enhanced Blockchain Technology As A Transformative Paradigm For Kenya, Addressing Finance, Corruption, And Voter Fraud.: From" Do No Evil" To" Can’t Do Evil" Ai-Enhanced Blockchain Technology As A Transformative Paradigm For Kenya. European Academic Journal-I, 3(001).
  22. Mwansa, P. (2023). Trust System Framework For Integrity Controls In Electoral Vote Counting And Validation. Cape Peninsula University Of Technology.
  23. Natale, S., & Ballatore, A. (2020). Imagining The Thinking Machine: Technological Myths And The Rise Of Artificial Intelligence. Convergence, 26(1), 3–18.
  24. Novelli, C., & Sandri, G. (2024). Digital Democracy In The Age Of Artificial Intelligence. Arxiv Preprint Arxiv:2412.07791.
  25. Ohize, H. O., Onumanyi, A. J., Umar, B. U., Ajao, L. A., Isah, R. O., Dogo, E. M., Nuhu, B. K., Olaniyi, O. M., Ambafi, J. G., & Sheidu, V. B. (2025). Blockchain For Securing Electronic Voting Systems: A Survey Of Architectures, Trends, Solutions, And Challenges. Cluster Computing, 28(2), 132.
  26. Peelam, M. S., Kumar, G., Shah, K., & Chamola, V. (2025). Democracyguard: Blockchain‐Based Secure Voting Framework For Digital Democracy. Expert Systems, 42(2), E13694.
  27. Rafi, M. (2025). Reimagining Democratic Elections: An Ai-Powered Techno-Democratic Republic. Available At Ssrn 5507579.
  28. Samoili, S., Cobo, M. L., Gómez, E., De Prato, G., Martínez-Plumed, F., & Delipetrev, B. (2020). Ai Watch. Defining Artificial Intelligence. Towards An Operational Definition And Taxonomy Of Artificial Intelligence.
  29. Simoes, S., & Maccarthaigh, M. (2023). Ai And Core Electoral Processes: Mapping The Horizons. Arxiv Preprint Arxiv:2302.03774.
  30. Sujatha, B., Ganesh, Y., Leelavathy, N., Tamilkodi, R., Venkatesh, S., Sandhya, B., & Kowshik, T. S. (2024). Blockchain-Powered E-Voting: A Novel Approach To Secure Voter Authentication, Online Voting And Election Automation. Indian Journal Of Science And Technology, 17(47), 4948–4958.
  31. Tussyadiah, I. (2020). A Review Of Research Into Automation In Tourism: Launching The Annals Of Tourism Research Curated Collection On Artificial Intelligence And Robotics In Tourism. Annals Of Tourism Research, 81, 102883.
  32. Zhuravlov, D. V, & Zhuravlov, D. D. (2025). Automated Complex" Electronic Signature Of The Voter (Epo)" As An Element Of The Critical Infrastructure Of The Election Process. Metaverse Science, Society And Law, 1(2).

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