• Review of KIISC
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• v.30 no.2
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• pp.5-9
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• 2020

널리 알려진 바와 같이 드론산업은 4차 산업혁명을 견인하는 13대 혁신성장 동력 산업 중 하나이다. 드론은 조종사가 탑승하지 않는 무인/원격조종 비행장치로 영상촬영, 감시, 조사, 물품배송 등의 서비스에 활용되고 있다. 드론을 이용한 서비스가 안전하게 상용화되기 위해서는 필수적으로 드론 자체 및 드론 기반 서비스를 보호하는 드론 보안기술이 적용되어야 한다. 드론은 피해자임과 동시에 가해자가 될 수 있는 양면성을 지니고 있기 때문에 이러한 특성을 고려한 보안기술이 필요하다. 최근 드론 보안의 양면성을 고려한 핵심요소로 드론식별모듈(DIM)이 개발되고 있다. 본 논문에서는 드론식별모듈 개념을 정의하고, 주요 기능 소개 및 국제표준화 추진 현황을 설명한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.203-205
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• 2023

최근 성장하고 있는 드론 산업에 맞추어 전세계적으로 드론 운용을 위한 식별 및 인증 규정을 마련하고 있는 추세이다. 대표적으로, 미국 FAA 에서 채택한 Remote ID 기반의 식별방식이 있다. 그러나, ID 기반의 인증 방식은 해당 ID 가 탈취 혹은 위조될 경우 다른 드론으로 위장하여 여러 심각한 사회 문제를 일으킬 위험성이 있다. 따라서 드론에 탑재된 여러 센서나 모터와 같은 하드웨어의 고유한 특성을 이용하여 Remote ID 를 대체하거나 이중 인증에 이용하려는 연구가 이루어지고 있다. 본 논문에서는 드론에 탑재된 하드웨어의 고유특성을 이용한 다양한 식별 및 인증시스템에 대한 연구에 대하여 살펴본다.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.18-25
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• 2020

This paper provides the basic data of low-altitude small drone management technology to solve the problem of drone's dysfunction that generally increases with the demand of the drone. Accordingly, various low-altitude small drone identification technology employed in many countries were investigated and analyzed. Herein, the research cases which have been developed to obtain diverse information such as the flight's plan, pilot's identity and contact number, and the flight's information such as the location and speed of small drones were mainly investigated. Furthermore, the list of the features of each case was analyzed. Moreover, the present paper suggests a drone identification system configuration which complements the problems of existing technologies and verifies the proposed system through a flight test.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.329-330
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• 2024

최근 드론 산업의 성장으로 드론 등록이 증가함에 따라 드론을 효율적으로 관리하기 위해 Remote ID를 도입하였다. 그러나 현재의 방법은 드론의 개인 정보 보호를 고려하지 않고 있어 드론의 개인 정보 노출과 보안 문제를 초래할 수 있다. 본 논문에서는 하드웨어의 고유 특성을 PUF 를 활용하여 드론의 익명성을 보호하고, 신뢰할 수 있는 대상이 드론을 안전하게 식별할 수 있도록 하는 새로운 프로토콜을 제안한다.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.133-143
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• 2023

As drones (also known as UAV) become popular with advanced information and communication technology (ICT), they have been utilized for various fields (agriculture, architecture, and so on). However, malicious attackers with advanced drones may pose a threat to critical national infrastructures. Thus, anti-drone systems have been developed to respond to drone threats. In particular, remote identification data (R-ID)-based UAV detection and identification systems that detect and identify illegal drones with R-ID broadcasted by drones have been developed, and are widely employed worldwide. However, this R-ID-based UAV detection/identification system is vulnerable to security due to wireless broadcast characteristics. In this paper, we analyze the security vulnerabilities of DJI Aeroscope, a representative example of the R-ID-based UAV detection and identification system, and propose a replay-attack-based neutralization method using the analyzed vulnerabilities. To validate the proposed method, it is implemented as a software program, and verified against four types of attacks in real test environments. The results demonstrate that the proposed neutralization method is an effective neutralization method for R-ID-based UAV detection and identification systems.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.639-644
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• 2024

Recent developments in the use of drones on battlefields, extending beyond reconnaissance to firepower support, have greatly increased the importance of technologies for early automatic drone identification. In this study, to identify an effective image classification model that can distinguish drones from other aerial targets of similar size and appearance, such as birds and balloons, we utilized a dataset of 3,600 images collected from the internet. We adopted a transfer learning approach that combines the feature extraction capabilities of three pre-trained convolutional neural network models (VGG16, ResNet50, InceptionV3) with an additional classifier. Specifically, we conducted a comparative analysis of the performance of these three pre-trained models to determine the most effective one. The results showed that the InceptionV3 model achieved the highest accuracy at 99.66%. This research represents a new endeavor in utilizing existing convolutional neural network models and transfer learning for drone identification, which is expected to make a significant contribution to the advancement of drone identification technologies.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1217-1228
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• 2023

In this paper, technical and patent analysses of anti-drone technology, which aim to neutralize drone attacks are conducted. We conducted research on the technical definition of anti-drone, the technical elements of anti-drone systems, and investigated the patents related to anti-drone and drone filed domestically and internationally over the past 10 years, starting from 2011. For domestic patents, we examined the number of patent applications related to anti-drone and the overall domestic patent applications over the past 10 years. Regarding international filings, we investigated the patent applications related to anti-drone filed in the United States, Europe, Japan, China, and under the PCT system in the past 10 years. We conducted a search for patents related to anti-drone, including neutralization techniques identified under the keyword "anti-drone," patents related to drone detection and identification techniques, and patents related to drone neutralization techniques. Through the conducted research, a total of 91 patents were filed for drone detection techniques. Out of these, 5 patents, accounting for 5.5%, were filed by public institutions. In the case of patents filed for drone identification techniques, there were a total of 174 patents. Among these, 4 patents, which is 2.3%, were filed by public institutions.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.186-187
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• 2016

본 논문에서는 평소 사람이 접근하기 어려워 점검이 힘들었던 대형구조물에 대하여 드론을 활용한 안전점검의 활용 가능성을 기획하였으며, 지상에서 식별하기 힘들거나 육안만으로 찾기 힘든 구조물을 근접 촬영하고 열화상 카메라를 이용해 구조물의 상태를 정밀 점검하고자 한다. 국내 최초로 드론을 활용하여 정밀 안전진단에 활용 가능한지에 대한 검토와 일반 안전진단과의 차별성 및 비교를 통해 향후 드론에 미치는 영향을 검토하고자 한다.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.604-611
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• 2016

Drone, which refers to unmanned aerial vehicles (UAV), industries are improving rapidly and exceeding existing level of remote controlled aircraft models. Also, they are applying automation and cloud network technology. Recently, the ability of drones can bring serious threats to public safety such as explosives and unmanned aircraft carrying hazardous materials. On the purpose of reducing these kinds of threats, it is necessary to detect these illegal drones, using acoustic feature extraction and classifying technology. In this paper, we introduce sound feature vector extraction method by harmonic feature extraction method (HLA). Feature vector extraction method based on HLA make it possible to distinguish drone sound, extracting features of sound data. In order to assess the performance of distinguishing sounds which exists in outdoor environment, we analyzed various sounds of things and real drones, and classified sounds of drone and others as simulation of each sound source.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.891-898
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• 2022

Along with global interest, drones are expanding the base of utilization such as transportation of goods, forest protection, and safety management, and cluster flights are being applied in various fields such as military operations and environmental monitoring. Currently, specialized networks such as e-UM 5G for services in specific industries are being established in Korea. In this regard, drone systems are also moving to establish specialized networks to provide services that are fused with AI and autonomous flight. As drones converge with various services, various security threats in various environments are also subordinated, and in response, requirements and guidelines for drone security are being prepared in Korea. In this paper, we propose a technology method for peer identification and safe information provision between cluster flight drones by utilizing a cryptographic module equipped with wireless LAN and quantum entropy-based random number generator in a cluster flight system and a mobile communication network such as e-UM 5G.