The increasing use of drones in terrorist attacks highlights the need for effective strategies to prevent and respond to drone terrorism. This study uses machine learning approach to identify factors that predict the success of drone terrorism and suggests policy alternatives for preventing such acts. Drone terrorism is becoming increasingly accessible due to advancements in information and communication technology, and events such as North Korea’s drone infiltration and the Russia-Ukraine war demonstrate the potential threat of drone attacks on Important National Facilities, including nuclear power plants. Using the Global Terrorism Database (GTD), this study analyzed drone terrorism incidents that occurred worldwide from 2016 to 2020. The study employed the Random Forest algorithm, which can incorporate multiple factors and their interactions, making it particularly suitable for social science research. The study provides new insights by deriving predictors that were previously overlooked in empirical analyses of drone terrorism. The findings of this study can aid in the establishment of anti-terrorism policies aimed at addressing the growing threat of drone terrorism. This can include the organization and expansion of the crisis management governance terrorism response council, the creation of a working manual through the partial revision of laws concerning drone terrorism response, and the implementation of anti-drone equipment and systems. Ultimately, the insights gained from this study can provide development of effective strategies aimed at preventing and responding to drone attacks. The study highlights the importance of proactive measures to mitigate the risks posed by drone technology in the context of terrorism.

As drone technology and industry develop around the world, the use of drones are increasing in number and expanding to different fields. On the other hand, illegal flight and terrorist incidents using drones are also increasing day by day. In Korea, it is reflected in the “Design Basis Threat (DBT)”, which is the standard for designing and evaluating the physical protection system of nuclear power plants in accordance with the “Act on Physical Protection and Radiological Emergency”, that nuclear power plants continue to establish physical protection against drone threats. A total of 141 drone attacks or incidents have occurred around the world since 2015. Cases related to the Russian-Ukraine war, in which so many cases occurred, were excluded. There were 112 cases (79%) of terrorism or suspected terrorism using a single drone. There were 4 cases of terrorism using more than 5 drones, and a total of 20 drones were used to attack an oil facility in Yemen (2019). By region, a total of 111 incidents occurred in Middle East & North Africa. By country, there were 49 cases in Iraq, 35 cases in Saudi Arabia, and 8 cases in Syria. Among major countries, three cases occured in Korea, five in the United States, two in England, Canada, and Italy, and one in Japan and France. Since 2021, there have been 15 drone attacks. Multiple drones were used in attacks targeting military or large-scale Important National Facilities such as the Saudi oil refinery, Indian Kashmir air base, and reconnaissance of Iranian Natanz nuclear and surrounding military facilities. Also in 89% of the cases, the drones were loaded with explosives in order to cause large-scale damage. Accordingly, nuclear power plants, which are important national facilities, need to establish a system that can detect and respond to multiple drones. Furthermore, additional protective measures are needed for areas that are expected to be severely damaged which can be established by evaluating the impact of explosives on major points in the plant. In additionthere is a high possibility of terrorism by organizations aiming for national turmoil rather than individual terrorists. So it is important to identify signs of terrorism in advance and prepare through cooperation with related agencies.