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.
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
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.
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)
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