The rapid advancement of information technologies has created numerous opportunities for human societies, but it has also introduced complex challenges. One of the most significant challenges is deepfake technology, which leverages deep learning algorithms to enable highly realistic manipulation of images, videos, and audio. While this technology offers positive applications in fields such as cinema and advertising, it poses a serious threat to national and societal security. Deepfakes can undermine public trust, incite social unrest, and weaken intelligence and security institutions. This article aims to examine the challenges posed by deepfake technology in intelligence and security operations and to propose strategies for mitigating its risks. The findings suggest that the development of intelligent detection tools, enhancing media literacy, and designing advanced authentication systems can play a pivotal role in reducing deepfake-related threats. Furthermore, recommendations are provided for leveraging emerging technologies to strengthen intelligence and operational security.
1. Ahmadi, A., Zargar, A., & Adami, A. (2022). The role of emerging technologies in the security and national power of countries: Opportunities and threats. International Studies Quarterly, 4, 139-159.
2. Al-San, M., & Dehestani, S. (2022). Legal aspects of deepfake technology. Legal Research Journal, 193-218.
3. Akbari, A., Aghapour, A., & Aghapour, K. (2022). Criminal analysis of deepfakes with a focus on Iranian criminal policy and human rights challenges. Scientific Workshop Quarterly, 59, 149-169.
4. Namjou, A., & Ahmadi, A. (2019). Methods of detecting deepfake videos using artificial neural networks. National Computer Engineering Conference, 1-8.
5. Rahmani Saeed, H., & Ebrahimi, H. (2018). The role of counterintelligence organizations in ensuring the political security of the Islamic Republic of Iran. Protective and Security Research Journal, 27, 55-82.
6. Nikmaleki, M. (2021). Deepfake: Fabrication of reality using artificial intelligence. News Research Journal of the Political Studies Department, 1-11.
منابع خارجی
1. Khan, I. R., Aisha, S., Kumar, D., & Mufti, T. (2023). A systematic review on deepfake technology. In Khanna, A., Polkowski, Z., Castillo, O. (Eds.), *Proceedings of Data Analytics and Management* (Vol. 572, pp. 7615-55). Springer, Singapore.
2. Han, J., Kamber, M., & Pei, J. (2011). Data mining: Concepts and techniques. Elsevier.
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. *AI Magazine, 17*(3), 37-54. https://doi.org/10.1609/aimag.v17i3.1230
Nosratabadi, J., Zavartorbati, A., & Esmaeilpour, E. (2024). Challenges and Strategies for Countering Deepfake Technology in the Realm of Security and Intelligence Activities. , 23(86), 29-50. doi: 10.22034/amn.2024.368
MLA
Jamshid Nosratabadi; Ahmad Zavartorbati; Esmaeil Esmaeilpour. "Challenges and Strategies for Countering Deepfake Technology in the Realm of Security and Intelligence Activities". , 23, 86, 2024, 29-50. doi: 10.22034/amn.2024.368
HARVARD
Nosratabadi, J., Zavartorbati, A., Esmaeilpour, E. (2024). 'Challenges and Strategies for Countering Deepfake Technology in the Realm of Security and Intelligence Activities', , 23(86), pp. 29-50. doi: 10.22034/amn.2024.368
VANCOUVER
Nosratabadi, J., Zavartorbati, A., Esmaeilpour, E. Challenges and Strategies for Countering Deepfake Technology in the Realm of Security and Intelligence Activities. , 2024; 23(86): 29-50. doi: 10.22034/amn.2024.368