• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.477-485
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• 2019

As the drones industry evolved, the security of the drone network has been important. In this paper, MTD (Moving Target Detection) technique is applied to the drone network for improving security. The existing MTD scheme has a risk that the hash value is exposed during the wireless communication process, and it is restricted to apply the one-to-many network. Therefore, we proposed PHT (Preposition Hash Table) scheme to prevent exposure of hash values during wireless communication. By reducing the risk of cryptographic key exposure, the use time of the cryptographic key can be extended and the security of the drone network will be improved. In addition, the cryptographic key exchange is not performed during flight, it is advantageous to apply PHT for a swarm drone network. Through simulation, we confirmed that the proposed scheme can contribute to the security of the drone network.

• Convergence Security Journal
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• v.18 no.2
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• pp.133-139
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• 2018

The 5 Game changer means the concepts of the army's operation against the enemy's asymmetric threats so that minimize damage to the public and leads to victory in war in the shortest time. A study of network architecture of Dronebot operation is a key study to carry out integrated operation with integrated C4I system by organically linking several drones battle groups through ICT. The NBC reconnaissance drones can be used instead of vehicles and humans to detect NBC materials and share situations quickly. However, there is still a lack of research on the swarm flight of the NBC reconnaissance drones and the weaknesses of cyber electronic warfare. In this study, we present weaknesses and countermeasures of CBRNs in swarm flight operations and provide a basis for future research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.156-164
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• 2019

In this paper, we propose an efficient dynamic slot re-assignment scheme for swarming drone networks in which networks members merged and split frequently. The leader drone of each network recognizes the slot allocation information of neighbor networks by periodic information exchange among between the drones. Using the information, the leader drone makes a decision how to reallocate the slots between members in case of network merge. The non-competitive method in the proposed scheme can re-assign the slots without any slot collision and shows always superior performance than competitive scheme. The competitive method in the proposed scheme reduces the number of slots that should be re-assigned in case of network merge. The experimental performance analysis shows that the proposed scheme performs better or at least equal to the performance of the competitive scheme in a swarming drone network.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.456-463
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• 2021

In this paper, Ultra Wide-Band(UWB) radar sensor is employed to detect flying drones and avoid collision in dense clutter environments. UWB signal is preferred when high resolution range measurement is required for moving targets. However, the time varying motion of flying drones may increase clutter noises in return signals and deteriorates the target detection performance, which lead to the performance degradation of anti-collision radars. We adopt a dynamic clutter suppression algorithm to estimate the time-varying distances to the moving drones with enhanced accuracy. A modified Constant False Alarm Rate(CFAR) is developed using an adaptive filter algorithm to suppress clutter while the false detection performance is well maintained. For this purpose, a velocity dependent CFAR algorithm is implemented to eliminate the clutter noise against dynamic target motions. Experiments are performed against flying drones having arbitrary trajectories to verify the performance improvement.

• Journal of KIISE
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• v.43 no.12
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• pp.1315-1324
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• 2016

Recently, the increasing interest in drones has resulted in development of new related technologies. Attention has been focused toward research on swarm flight which controls drones simultaneously without collision. Thus, complicated missions can be completed rapidly through collaboration between drones. Due to low position accuracy, GPS is not appropriate for the outdoor mission involving accurate flight. In addition, the inaccurate position estimation of GPS gives rise to the serious problem of collision, since many drones are controlled in a narrow space. In this study, we increased the accuracy of position estimation through various sensors with Real-Time Kinematic-GPS (RTK-GPS). The mode switching algorithm was proposed to minimize the problem of sensor error. In addition, we introduced the outdoor swarm flight system based on the proposed position estimation.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• Annual Conference of KIPS
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• 2019.10a
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• pp.192-194
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• 2019

드론을 이용한 영상 촬영이 대두되고 있는 현재에 효율적으로 영상을 전송하기 위한 대역폭이나 네트워크 시스템을 연구해야할 필요성이 있으며 2대 이상의 멀티 드론을 동기화 및 군집화 시키기 위한 라우팅 프로토콜을 설계하려 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.41-46
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• 2019

In this paper, it is necessary to study the bandwidth and network system for efficient image transmission in the current era of drone imaging, and to design routing protocols to round out and cluster two or more multi-drones. First, we want to construct an ad hoc network to control the multidrone. Several studies are underway for the clustering of drones. The aircraft ad hoc network (FANET) is an important foundation for this research. A number of routing protocols have been proposed to design a FANET, and these routing protocols show different performances in various situations and environments. The routing protocol used to design the FANET is tested using the routing protocol used in the existing mobile ad hoc network (MANET). Therefore, we will use MANET to simulate the routing protocol to be used in the FANET, helping to select the optimal routing protocol for future FANET design. Finally, this paper describes the routing protocols that are mainly used in MANET and suitable for FANET, and the performance comparison of routing protocols, which are mainly used in FANET design.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.245-246
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• 2019

본 논문에서는 GUI(Graphical User Interface)를 이용하여 다수의 드론을 동시 제어하는 시스템 구현 결과를 보인다. 네트워크 소켓(Network Socket) 응용 프로그램인 Packet Sender를 이용하여 다수의 드론을 AP(Wireless Access Point)에 연결하였다. Python 응용 프로그램으로 UDP(User Datagram Protocol) 소켓을 통해 AP에 연동된 드론으로 명령을 전송하여 제어한다. Python GUI 모듈인 Tkinter를 이용하여 사용자에게 GUI를 제공함으로써 접근성(Accessibility)을 높인 시스템을 개발하였다.