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ASSESSING THE UNRELIABILITY OF ONLINE POLITICAL POLLS: A NOVEL SOFTWARE FOR VOTING APPROACH

Yıl 2024, Cilt: 12 Sayı: 2, 539 - 552, 31.12.2024

Murat Işık , Mehmet Ali Yalçınkaya

https://doi.org/10.52122/nisantasisbd.1478942

Öz

In recent years, the utilization of online polls for political opinion sampling has become prevalent due to their cost-effectiveness and rapid deployment. However, their reliability is frequently questioned due to vulnerabilities inherent in their digital nature. This study explores the susceptibility of online polls to manipulation, examining the efficacy of various security measures employed across 160 online polling platforms during the 2024 municipal elections in Turkey. Through automated voting on these platforms, which encompassed a total of 10,000 votes, significant security flaws were uncovered. The findings reveal that while measures such as CAPTCHA, digital fingerprint, and IP validation offer some resistance, they are not foolproof. It is concluded that the most robust method involves verifying users via the e-government platform, enhancing both the credibility and integrity of online polls. This study not only highlights the vulnerabilities of current online polling practices but also provides a roadmap for enhancing security to better reflect genuine public opinion and foster more trustworthy political decision-making processes.

Anahtar Kelimeler

online polls digital fingerprint IP validation automatic votes

Kaynakça

  • Anderson, B., & McGrew, D. (2017). OS fingerprinting: New techniques and a study of information gain and obfuscation. 2017 IEEE Conference on Communications and Network Security (CNS). https://doi.org/10.1109/CNS.2017.8228665
  • Basso, A., & Miraglia, M. (2008). Avoiding massive automated voting in internet polls. Electronic Notes in Theoretical Computer Science, 197(2), 149-157. https://doi.org/10.1016/j.entcs.2007.12.024
  • Boda, K., Földes, Á. M., Gulyás, G. G., & Imre, S. (2012). User tracking on the web via cross-browser fingerprinting. Information Security Technology for Applications: 16th Nordic Conference on Secure IT Systems, NordSec 2011. https://doi.org/10.1007/978-3-642-27937-9_5
  • Das, A., Dutta, M. P., & Banerjee, S. (2016). VOT-EL: Three-tier secured state-of-the-art EVM design using pragmatic fingerprint detection annexed with NFC-enabled voter-ID card. 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). https://doi.org/10.1109/ICETETS.2016.7603021
  • Köse, E. (2019). “App Store’daki uygulamaların indirilme sayıları işte böyle manipüle ediliyor.” Retrieved from https://www.log.com.tr/app-storedaki-uygulamalarin-indirilme-sayilari-iste-boyle-manipule-ediliyor/
  • Fifield, D., & Egelman, S. (2015). Fingerprinting web users through font metrics. Financial Cryptography and Data Security: 19th International Conference, FC 2015. https://doi.org/10.1007/978-3-662-47854-7_10
  • Gajani, Y. K., Bhardwaj, S., & Thenmozhi, M. (2023). Guarding against bots with art: NST-based deep learning approach for CAPTCHA verification. 2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI). https://doi.org/10.1109/RAEEUCCI2023.9912054
  • Hargittai, E., & Karaoglu, G. (2018). Biases of online political polls: Who participates? Socius, 4. https://doi.org/10.1177/2378023118791080
  • Iqbal, U., Englehardt, S., & Shafiq, Z. (2021). Fingerprinting the fingerprinters: Learning to detect browser fingerprinting behaviors. 2021 IEEE Symposium on Security and Privacy (SP). https://doi.org/10.1109/SP50901.2021.00051
  • Kennedy, C., Hatley, N., Lau, A., Mercer, A., Keeter, S., Ferno, J., & Asare-Marfo, D. (2021). Strategies for detecting insincere respondents in online polling. Public Opinion Quarterly, 85(4), 1050-1075. https://doi.org/10.1093/poq/nfab057
  • Laperdrix, P., Bielova, N., Baudry, B., & Avoine, G. (2020). Browser fingerprinting: A survey. ACM Transactions on the Web (TWEB), 14(2), 1-33. https://doi.org/10.1145/3386040
  • Martin, S., & Geiger, S. (1999). Building relationships? The marketing of political parties in cyberspace. Academy of Marketing Special Interest Group Political Marketing Conference.
  • Mohammadi, S., & Abbasimehr, H. (2010). A high-level security mechanism for internet polls. 2010 2nd International Conference on Signal Processing Systems. https://doi.org/10.1109/ICSPS.2010.5555606
  • Mondal, S., Rana, R., Pawar, L., Vishwakarma, A., & Lokhande, P. S. (2023). Referendum poll system: A blockchain-based solution for direct democracy. Available at SSRN. https://doi.org/10.2139/ssrn.4398651
  • Natarajan, V. (2024). Online voting system using AES algorithm with OTP validation. International Research Journal on Advanced Engineering Hub (IRJAEH), 2(02), 57-61.
  • Nikiforakis, N., Kapravelos, A., Joosen, W., Kruegel, C., Piessens, F., & Vigna, G. (2013). Cookieless monster: Exploring the ecosystem of web-based device fingerprinting. 2013 IEEE Symposium on Security and Privacy. https://doi.org/10.1109/SP.2013.28
  • Park, S., Specter, M., Narula, N., & Rivest, R. L. (2021). Going from bad to worse: From internet voting to blockchain voting. Journal of Cybersecurity, 7(1), 1-15. https://doi.org/10.1093/cybsec/tyaa025
  • Pekar, V., Najafi, H., Binner, J. M., Swanson, R., Rickard, C., & Fry, J. (2022). Voting intentions on social media and political opinion polls. Government Information Quarterly, 39(4), 101658. https://doi.org/10.1016/j.giq.2021.101658
  • Prabhu, S. G., Nizarahammed, A., Prabu, S., Raghul, S., Thirrunavukkarasu, R., & Jayarajan, P. (2021). Smart online voting system. 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). https://doi.org/10.1109/ICACCS51430.2021.9441917
  • Qureshi, A., Megias, D., & Rifà-Pous, H. (2019). SeVEP: Secure and verifiable electronic polling system. IEEE Access, 7, 19266-19290. https://doi.org/10.1109/ACCESS.2019.2897252
  • Sai, M. H., & Kumar, V. A. (2022). Online voting system using Java and SQL. In Proceedings of the International Conference on Advanced Computing and Communication Systems (ICACCS) (pp. 910-913).
  • Shalini, S., Rachel, A. S., & Roshinee, A. (2020). Tracking real-time vehicle and locking system using LabVIEW applications. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). https://doi.org/10.1109/ICACCS48705.2020.9074241
  • Shao, R., Shi, Z., Yi, J., Chen, P.-Y., & Hsieh, C.-J. (2022). Robust text CAPTCHAs using adversarial examples. 2022 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData55660.2022.10020482
  • Sivasakthi, T., Shivani, V., Palani, U., Vasanthi, D., Roshini, S., & Saundariya, K. (2021). Development of E-polling website using MERN. 2021 Smart Technologies, Communication and Robotics (STCR). https://doi.org/10.1109/STCR53369.2021.9682226
  • Stantcheva, S. (2023). How to run surveys: A guide to creating your own, identifying variation, and revealing the invisible. Annual Review of Economics, 15, 205-234. https://doi.org/10.1146/annurev-economics-091622-010157
  • Tsingenopoulos, I., Preuveneers, D., Desmet, L., & Joosen, W. (2022). CAPTCHA me if you can: Imitation games with reinforcement learning. 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P). https://doi.org/10.1109/EuroSP53844.2022.00019
  • Wang, P., Gao, H., Xiao, C., Guo, X., Gao, Y., & Zi, Y. (2023). Extended research on the security of visual reasoning CAPTCHA. IEEE Transactions on Dependable and Secure Computing, 20(6), 4976-4992. https://doi.org/10.1109/TDSC.2022.3147489
  • Wang, Y., & Lu, M. (2016). A self-adaptive algorithm to defeat text-based CAPTCHA. 2016 IEEE International Conference on Industrial Technology (ICIT). https://doi.org/10.1109/ICIT.2016.7474812
  • Yeargain, T. (2020). Fake polls, real consequences: The rise of fake polls and the case for criminal liability. Missouri Law Review, 85, 129. Retrieved from https://scholarship.law.missouri.edu/mlr/vol85/iss1/7
  • Yudin, G. (2020). Governing through polls: Politics of representation and presidential support in Putin's Russia. Javnost-The Public, 27(1), 2-16. https://doi.org/10.1080/13183222.2020.1675434

Çevrimiçi Siyasi Anketlerin Güvenilirliğinin Değerlendirilmesi: Yeni Bir Oylama Yazılımı Kullanımı

Yıl 2024, Cilt: 12 Sayı: 2, 539 - 552, 31.12.2024

Murat Işık , Mehmet Ali Yalçınkaya

https://doi.org/10.52122/nisantasisbd.1478942

Öz

Son yıllarda, maliyet avantajı ve hızlı uygulanabilirliği nedeniyle siyasi görüş örneklemesi için çevrimiçi anketlerin kullanımı yaygınlaşmıştır. Ancak, bu anketlerin dijital ortamda olmasından kaynaklanan zaaflar nedeniyle güvenilirlikleri sıklıkla sorgulanmaktadır. Bu çalışma, Türkiye'deki 2024 yerel seçimleri sırasında 160 çevrimiçi anket platformunda uygulanan çeşitli güvenlik önlemlerinin etkinliğini inceleyerek çevrimiçi anketlerin manipülasyona ne kadar açık olduğunu araştırmaktadır. Çalışma kapsamında geliştirilen bir oylama uygulaması ile çalışmaya konu olan sitelerde 143 saatte 10.000 adet oy kullanılmıştır. Bulgular, CAPTCHA, dijital parmak izi ve IP doğrulama gibi önlemlerin bir miktar direnç sunduğunu, ancak bunların da kusursuz olmadığını ortaya koymaktadır. En güçlü yöntemin kullanıcıların e-devlet platformu üzerinden doğrulanması olduğu sonucuna varılmıştır. Bu çalışma, mevcut çevrimiçi anket uygulamalarının zaaflarını vurgulamakla kalmamakta, aynı zamanda kamuoyunun gerçek fikirlerinin daha iyi yansıtılabilmesi ve daha güvenilir siyasi kararlar alma süreçleri için bir yol haritası sunmaktadır.

Anahtar Kelimeler

çevrimiçi anketler dijital parmak izi IP doğrulama otomatik oylama

Kaynakça

  • Anderson, B., & McGrew, D. (2017). OS fingerprinting: New techniques and a study of information gain and obfuscation. 2017 IEEE Conference on Communications and Network Security (CNS). https://doi.org/10.1109/CNS.2017.8228665
  • Basso, A., & Miraglia, M. (2008). Avoiding massive automated voting in internet polls. Electronic Notes in Theoretical Computer Science, 197(2), 149-157. https://doi.org/10.1016/j.entcs.2007.12.024
  • Boda, K., Földes, Á. M., Gulyás, G. G., & Imre, S. (2012). User tracking on the web via cross-browser fingerprinting. Information Security Technology for Applications: 16th Nordic Conference on Secure IT Systems, NordSec 2011. https://doi.org/10.1007/978-3-642-27937-9_5
  • Das, A., Dutta, M. P., & Banerjee, S. (2016). VOT-EL: Three-tier secured state-of-the-art EVM design using pragmatic fingerprint detection annexed with NFC-enabled voter-ID card. 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). https://doi.org/10.1109/ICETETS.2016.7603021
  • Köse, E. (2019). “App Store’daki uygulamaların indirilme sayıları işte böyle manipüle ediliyor.” Retrieved from https://www.log.com.tr/app-storedaki-uygulamalarin-indirilme-sayilari-iste-boyle-manipule-ediliyor/
  • Fifield, D., & Egelman, S. (2015). Fingerprinting web users through font metrics. Financial Cryptography and Data Security: 19th International Conference, FC 2015. https://doi.org/10.1007/978-3-662-47854-7_10
  • Gajani, Y. K., Bhardwaj, S., & Thenmozhi, M. (2023). Guarding against bots with art: NST-based deep learning approach for CAPTCHA verification. 2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI). https://doi.org/10.1109/RAEEUCCI2023.9912054
  • Hargittai, E., & Karaoglu, G. (2018). Biases of online political polls: Who participates? Socius, 4. https://doi.org/10.1177/2378023118791080
  • Iqbal, U., Englehardt, S., & Shafiq, Z. (2021). Fingerprinting the fingerprinters: Learning to detect browser fingerprinting behaviors. 2021 IEEE Symposium on Security and Privacy (SP). https://doi.org/10.1109/SP50901.2021.00051
  • Kennedy, C., Hatley, N., Lau, A., Mercer, A., Keeter, S., Ferno, J., & Asare-Marfo, D. (2021). Strategies for detecting insincere respondents in online polling. Public Opinion Quarterly, 85(4), 1050-1075. https://doi.org/10.1093/poq/nfab057
  • Laperdrix, P., Bielova, N., Baudry, B., & Avoine, G. (2020). Browser fingerprinting: A survey. ACM Transactions on the Web (TWEB), 14(2), 1-33. https://doi.org/10.1145/3386040
  • Martin, S., & Geiger, S. (1999). Building relationships? The marketing of political parties in cyberspace. Academy of Marketing Special Interest Group Political Marketing Conference.
  • Mohammadi, S., & Abbasimehr, H. (2010). A high-level security mechanism for internet polls. 2010 2nd International Conference on Signal Processing Systems. https://doi.org/10.1109/ICSPS.2010.5555606
  • Mondal, S., Rana, R., Pawar, L., Vishwakarma, A., & Lokhande, P. S. (2023). Referendum poll system: A blockchain-based solution for direct democracy. Available at SSRN. https://doi.org/10.2139/ssrn.4398651
  • Natarajan, V. (2024). Online voting system using AES algorithm with OTP validation. International Research Journal on Advanced Engineering Hub (IRJAEH), 2(02), 57-61.
  • Nikiforakis, N., Kapravelos, A., Joosen, W., Kruegel, C., Piessens, F., & Vigna, G. (2013). Cookieless monster: Exploring the ecosystem of web-based device fingerprinting. 2013 IEEE Symposium on Security and Privacy. https://doi.org/10.1109/SP.2013.28
  • Park, S., Specter, M., Narula, N., & Rivest, R. L. (2021). Going from bad to worse: From internet voting to blockchain voting. Journal of Cybersecurity, 7(1), 1-15. https://doi.org/10.1093/cybsec/tyaa025
  • Pekar, V., Najafi, H., Binner, J. M., Swanson, R., Rickard, C., & Fry, J. (2022). Voting intentions on social media and political opinion polls. Government Information Quarterly, 39(4), 101658. https://doi.org/10.1016/j.giq.2021.101658
  • Prabhu, S. G., Nizarahammed, A., Prabu, S., Raghul, S., Thirrunavukkarasu, R., & Jayarajan, P. (2021). Smart online voting system. 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS). https://doi.org/10.1109/ICACCS51430.2021.9441917
  • Qureshi, A., Megias, D., & Rifà-Pous, H. (2019). SeVEP: Secure and verifiable electronic polling system. IEEE Access, 7, 19266-19290. https://doi.org/10.1109/ACCESS.2019.2897252
  • Sai, M. H., & Kumar, V. A. (2022). Online voting system using Java and SQL. In Proceedings of the International Conference on Advanced Computing and Communication Systems (ICACCS) (pp. 910-913).
  • Shalini, S., Rachel, A. S., & Roshinee, A. (2020). Tracking real-time vehicle and locking system using LabVIEW applications. 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). https://doi.org/10.1109/ICACCS48705.2020.9074241
  • Shao, R., Shi, Z., Yi, J., Chen, P.-Y., & Hsieh, C.-J. (2022). Robust text CAPTCHAs using adversarial examples. 2022 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/BigData55660.2022.10020482
  • Sivasakthi, T., Shivani, V., Palani, U., Vasanthi, D., Roshini, S., & Saundariya, K. (2021). Development of E-polling website using MERN. 2021 Smart Technologies, Communication and Robotics (STCR). https://doi.org/10.1109/STCR53369.2021.9682226
  • Stantcheva, S. (2023). How to run surveys: A guide to creating your own, identifying variation, and revealing the invisible. Annual Review of Economics, 15, 205-234. https://doi.org/10.1146/annurev-economics-091622-010157
  • Tsingenopoulos, I., Preuveneers, D., Desmet, L., & Joosen, W. (2022). CAPTCHA me if you can: Imitation games with reinforcement learning. 2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P). https://doi.org/10.1109/EuroSP53844.2022.00019
  • Wang, P., Gao, H., Xiao, C., Guo, X., Gao, Y., & Zi, Y. (2023). Extended research on the security of visual reasoning CAPTCHA. IEEE Transactions on Dependable and Secure Computing, 20(6), 4976-4992. https://doi.org/10.1109/TDSC.2022.3147489
  • Wang, Y., & Lu, M. (2016). A self-adaptive algorithm to defeat text-based CAPTCHA. 2016 IEEE International Conference on Industrial Technology (ICIT). https://doi.org/10.1109/ICIT.2016.7474812
  • Yeargain, T. (2020). Fake polls, real consequences: The rise of fake polls and the case for criminal liability. Missouri Law Review, 85, 129. Retrieved from https://scholarship.law.missouri.edu/mlr/vol85/iss1/7
  • Yudin, G. (2020). Governing through polls: Politics of representation and presidential support in Putin's Russia. Javnost-The Public, 27(1), 2-16. https://doi.org/10.1080/13183222.2020.1675434
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yönetim Bilişim Sistemleri, Bilgi Sistemleri (Diğer)
Bölüm Makaleler
Yazarlar

Murat Işık 0000-0003-3200-1609

Mehmet Ali Yalçınkaya 0000-0002-7320-5643

Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 5 Mayıs 2024
Kabul Tarihi 28 Ağustos 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 12 Sayı: 2

Kaynak Göster

APA Işık, M., & Yalçınkaya, M. A. (2024). ASSESSING THE UNRELIABILITY OF ONLINE POLITICAL POLLS: A NOVEL SOFTWARE FOR VOTING APPROACH. Nişantaşı Üniversitesi Sosyal Bilimler Dergisi, 12(2), 539-552. https://doi.org/10.52122/nisantasisbd.1478942
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