• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.327-332
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• 2023

On December 26, 2022, North Korea's drone provocation resumed for the first time in eight years. The threat covered not only the Seoul metropolitan area but also the no-fly zone for the presidential office's security, and the South Korean military's response to it is not appropriate, which is a major controversy. In the midst of this, problems caused by the prohibition of small drones' flight and illegal intrusion into restricted areas are increasing in Korea, and the threat is becoming a reality, such as being used for terrorist attacks abroad. In this paper, the concept of "Counter-Drone" and related technologies were considered for these drone threats, and implications were derived through domestic and overseas small drone threats, and the direction of development of the Counter-Drone system was presented. North Korea's drone threat is expected to be more diversified, massified, and advanced, resulting in bolder attacks and provocations. Therefore, the South Korean military should push for early powering of the integrated control system and the conter drone system, joint and military cooperation in response to the threat of small drones, and the ability to carry out joint operations between South Korea and the U.S.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.115-127
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• 2023

In this paper, we have undertaken a comprehensive investigation into the current state of anti-drone technology due to the increasing concerns and risks associated with the widespread use of drones. We carefully analyze anti-drone technology, dividing it into three crucial domains: detection, identification, and neutralization methods. This categorization enables us to delve into intricate technical details, highlighting the diverse techniques used to counter evolving drone threats. Additionally, we explore the legal and regulatory aspects of implementing anti-drone technology. Our research also envisions potential directions for advancing and evolving anti-drone tech to ensure its effectiveness in an ever-changing threat environment.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.23-36
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• 2021

Recently, the rapid development of drones is increasing as a variety of threats to important facilities of the country. In order to build an anti-drone system that responds to drones with high technical characteristics, standardization is required in terms of operation, system, and technology. By applying the defense architecture framework, it contributes to the establishment of the optimal system by proposing a standardization plan for the operational and system perspectives of the anti-drone system by creating outputs equivalent to the stage of prior research on weapons systems. It is a prerequisite for building a drone system the operational concept of the anti-drone system, the definition of the drone threat, the function of each component, the interface, the definition of data flow, the system performance and effect scale, etc. Management, security officers, and equipment manufacturers of important national and public facilities on site expect that it will be used as an objective standard at the government level for the component technology of the equipment to respond to the drone threat and the performance required in the environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.3
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• pp.591-605
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• 2022

As drones are widely used, attack attempts using drone vulnerabilities are increasing, and drone security is growing in importance. This paper derives security requirements for reconnaissance drone delivered to government office through threat modeling. Threats are analyzed by the data flow of the drone and collecting possible vulnerabilities. Attack tree is built by analyzed threats. The security requirements were derived from the attack tree and compared with the security requirements suggested by national organizations. Utilizing the security requirements derived from this paper will help in the development and evaluation of secure drones.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.93-104
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• 2023

Recently, the technology of drones is developing remarkably. The role of military drones is so great that they can cause serious damage to the enemy's important strategic assets without any damage to our allies in all battlefield environments (land, sea, air). However, the battleship combat management system currently operated by the Korean Navy is vulnerable to defense because there is no customized defense system against drones. As drones continue to develop, they are bound to pose a major threat to navy in the future. This paper proposes a way for the warfare software of naval combat management system sets a combat mode suitable for anti-drone battle, evaluates the threat priority in order to preemptively respond to drone threats and eliminate drone threats through automatic allocation of self-ship-mounted weapons and sensors, and through a test of the improved warfare software in a simulated environment, it was proved that the time to respond to the drone was improved by 62%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.4
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• pp.633-646
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• 2023

The increases in UAVs(Unman Aerial Vehicle) such as drone result in safety issues and the threat of illegal drone as well. Recognizing the need for Drone forensics, domestic and foreign organizations and agencies are trying to establish drone forensic guidelines. The definition of Drone forensic artifacts and examination of forensic tools must be provided, in order to establish a practical drone forensic framework on security sites and also the concept of drone live forensic which provides meaningful data that can be extracted in a live state. In this study, the drone forensic methodology covering various types of drones is explained, and the practical forensic methodology with live forensic PoC(Proof Of Concept) tools; LiPFo(Live-PX4-Forenensic) is proposed.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.319-320
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• 2023

본 논문은 이러한 국가중요시설에서의 드론테러 위협과 대응실태를 분석하여 문제점을 도출함으로써 안티드론시스템을 실효적으로 활용하기 위한 법·제도적 발전방안을 제시하는 데에 연구의 목적으로 두었다. 연구방법은 질적연구방법으로서 기존 선행연구논문, 정책자료 등에서 다루지 못한 다양한 문제점들을 전문가 심층면담을 통해 분석하였다. 심층면담을 위한 연구참여자는 국내 안티드론 및 테러분야 전문가 16명을 선정하여 반구조화 인터뷰 12개 문항을 토대로 진행하였다. 연구결과 현재 우리나라 국가중요시설 드론테러에 대해 효과적으로 대응하기 위해서 선행되어야 할 4 가지 문제점에 대한 개선사항이 식별되었다.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.