TERÖRLE MÜCADELEDE VERİNİN KULLANIMI

Yıl 2024, , 335 - 364, 29.11.2024

İrem Doğan , Muhammed Hayati Taban

https://doi.org/10.28956/gbd.1531048

Öz

Terör, uzun yıllar boyunca insanlığın karşılaştığı bir güvenlik sorunu olmuştur. Teknoloji çağının gereği yapay zekanın ve veri analizi yöntemlerinin uygulama alanı genişledikçe, bu araçların terörle mücadeledeki etkileri de kendini göstermeye başlamıştır. Bu makalede, Türkiye’de yaşanan terör olaylarının il bazında ilişkilendirilebilecek değişkenler incelenmiştir. Türkiye özelinde il bazında detaylı bir analiz sunarak, yerel dinamiklerin ve değişkenlerin terör olayları üzerindeki etkisini incelenmiştir. Bu çerçevede çalışma, veri odaklı yaklaşımların yerel düzeyde nasıl uygulanabileceğine dair önemli bulgular sunmaktadır. Terörle mücadelede teknolojinin ön plana çıkarılmasını vurgulanmıştır. Veri analizi, makine öğrenimi ve yapay zekâ gibi teknolojilerin kullanımı, terör eylemlerinin önceden tespit edilmesi ve engellenmesi konusunda büyük avantajlar sağlamaktadır. Bu bağlamda makale, Türkiye’nin veri kullanımın ön plana çıktığı teknolojilere yatırım yaparak ve veri odaklı stratejiler geliştirerek terörle mücadelede daha etkin sonuçlar elde edebileceğini göstermektedir. Çalışma ile, terörle mücadelede veri dünyasının sunduğu farklı yöntemler ve stratejilerin etkilerini anlamak için bir çerçeve oluşturulmuştur. Bu amaç doğrultusunda, 81 ile ilişkin elde edilen veriler kullanılarak, sonuçların gelecekteki mücadele stratejilerine katkı sağlaması hedeflenmektedir.

Anahtar Kelimeler

Terör, Terörle Mücadele, Veri, İstihbarat, Analiz

Use of Data in the Counte- Terrorism

Öz

Terrorism has been a security problem faced by humanity for many years. As the application area of artificial intelligence and data analysis methods has expanded as a requirement of the technological age, the effects of these tools in the counter- terrorism have also begun to manifest themselves. In this article, the variables that can be associated with terrorist incidents in Turkey on a province basis are analyzed. By presenting a detailed analysis on a province-by-province basis in Turkey, it examines the impact of local dynamics and variables on terrorist incidents. In this framework, the study provides important findings on how data-driven approaches can be applied at the local level. It is emphasized that technology should be brought to the forefront in the fight against terrorism. The use of technologies such as data analysis, machine learning and artificial intelligence provides great advantages in detecting and preventing terrorist acts in advance. In this context, the article shows that Turkey can achieve more effective results in the counter- terrorism by investing in data-driven technologies and developing data-driven strategies. The study provides a framework for understanding the effects of different methods and strategies offered by the data world in the counter- terrorism. In line with this purpose, the study aims to contribute to future counterterrorism strategies by using the data obtained from 81 provinces.

Anahtar Kelimeler

Terrorism, Counterterrorism, Data, Intelligence, Analysis

Kaynakça

• Action on Armed Violence (AOAV). (2024). https://aoav.org.uk/, [Erişim Tarihi: 05.02.2024].
• Adelaja, A., & George, J. (2020). Is youth unemployment related to domestic terrorism?. Perspectives on terrorism, 14(5), 41-62.
• Atsa’am, D. D., Wario, R., Okpo, F. E (2020). “A New Terrorism Categorization Based on Casualties and Consequences Using Hierarchical Clustering”. Journal of applied security research, 15 (3), 369-384.
• Adıgüzel, F., Dereli, C., & Karagöz, P. (2022). Erişime Açık Terörizm Veri Kümeleri Kullanarak Makine Öğrenmesi ve Büyük Veri Mimarileri ile Terörle Mücadeleye Yönelik Tahminleme Yaklaşımları. Savunma Bilimleri Dergisi, (42), 119-154.
• Bhuyan, Hemanta Kumar. Subhendu Kumar Pani (2021). Crime Predictive Model Using Big Data Analytics. IEEE, 57-78.
• Chung, S., & Shannon, M. (2005). Hospital planning for acts of terrorism and other public health emergencies involving children. Archives of disease in childhood, 90(12), 1300-1307.
• Claassen, C. A., Carmody, T., Stewart, S. M., Bossarte, R. M., Larkin, G. L., Woodward, W. A., & Trivedi, M. H. (2010). Effect of 11 September 2001 terrorist attacks in the USA on suicide in areas surrounding the crash sites. The British Journal of Psychiatry, 196(5), 359-364.
• Coccia, M. (2018 b). “What Is The Growth Rate Of Population That Supports Terrorism in Regions With Social Issues?”, Coccialab Working Papers, C.37, (2018): 10.
• Coccia, M. (2018 a). The relation between terrorism and high population growth. Journal of Economics and Political Economy, 5(1), 84-104.
• Fadare, O., Zanello, G., & Srinivasan, C. (2022). The joint effects of terrorism and land access on livestock production decisions: Evidence from northern Nigeria. World Development Perspectives, 27, 100447.
• Global Terrorism Database. (2024). https://www.start.umd.edu/gtd/about/ [Erişim Tarihi: 06.02.2024].
• Goldstein, K. B. (2005). Unemployment, inequality and terrorism: Another look at the relationship between economics and terrorism. Undergraduate Economic Review, 1(1), 6.
• Helbling, M., & Meierrieks, D. (2022). Terrorism and migration: An overview. British Journal of Political Science, 52(2), 977-996.
• Hulnick, A. S. (2006). What's wrong with the Intelligence Cycle. Intelligence and national Security, 21(6), 959-979.
• Korotayev, A., Romanov, D., Zinkina, J., & Slav, M. (2023). Urban youth and terrorism: A quantitative analysis (are youth bulges relevant anymore?). Political Studies Review, 21(3), 548-572.
• LaFree, G., & Bersani, B. E. (2014). County‐level correlates of terrorist attacks in the United States. Criminology & Public Policy, 13(3), 455-481.
• LaFree, G., & Dugan, L. (2007). Introducing the global terrorism database. Terrorism and political violence, 19(2), 181-204.
• May, Thomas., P. Aulisio, Mark. (2006). Access to Hospitals in the Wake of Terrorism: Challenges and Needs for Maintaining Public Confidence. Disaster Management & Response. 4, 67-71.
• Meng, Xi., Nie, Lingyu., Song, Jiapeng. “Big data-based prediction of terrorist attacks”. Computers and Electrical Engineering, (77), 120-127.
• Meierrieks, D., & Schaub, M. (2024). Terrorism and child mortality. Health Economics, 33(1), 21-40.
• Nie, Sanjun. Duoyong Sun. “Research on Counter-Terrorism Based on Big Data”. Computers and Electrical Engineering, C. 77 (2019): 120-127.
• Orkar, O. M. D., Tyungu, G. T., & Shaminja, T. S. (2020). Examining The Nexus Between Illiteracy And Terrorism In Nigeria: Borno State North-Eastern, Nigeria In Perspective. International journal of Innovative Research and Advanced Studies (IJRAS), 7 (9), 32-36.
• Qu, Y., Chen, Y., Tan, Z., & Han, B. (2024). “The Statistical Analysis Based on GTD Terrorist Incident Record Data”, Journal Pre-Proof, 10.
• Ulaş, Mustafa, Barış Karabay. “Terör Saldırılarını İçeren Büyük Verinin Makine Öğrenmesi Teknikleri ile Analizi”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, C. 32, S. 1 (2020): 267-277.
• Terörizm Analiz Platformu (TAP). (2024). https://tap-data.com/ [Erişim Tarihi: 06.02.2024].
• The Armed Conflict Location & Event Data Project (ACLED). (2024). https://acleddata.com/, [Erişim Tarihi: 05.02.2024].
• The RAND Database of Worldwide Terrorism Incidents (RDWTI). (2024). https://www.rand.org/nsrd/projects/ terrorism-incidents.html, [Erişim Tarihi: 05.02.2024].
• Townsend, E. (2007). Suicide terrorists: Are they suicidal?. Suicide and Life-Threatening Behavior, 37(1), 35-49.
• Verhelst, H. M. A. W. Stannat, G. Mecacci. “Machine Learning Against Terrorism:
• How Big Data Collection and Analysis Influences the Privacy‑Security
• Dilemma”. Science and Engineering Ethics, C. 26 (2020): 975-2984.
• Wagner, Z., Heft-Neal, S., Bhutta, Z. A., Black, R. E., Burke, M., & Bendavid, E. (2018). Armed conflict and child mortality in Africa: a geospatial analysis. The Lancet, 392(10150), 857-865.
• Yang, H. L. (2022, December). Application of Big Data in Counter-Terrorism Intelligence Analysis and Early Warning. In 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022) (pp. 1193-1200). Atlantis Press