• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.186-186
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• 2022

과거에는 선박을 운용하기 위해서 많은 인원이 필요하였으나 최근 들어 선박 운용에 필요한 인원이 줄어들고 있으며, 더 나아가 자율적으로 운항하는 선박을 만들기 위한 연구가 활발히 수행되고 있다. 자율 운항 선박을 구성하는 여러 요소 중 인간의 시각을 대체하기 위한 자율 인지 시스템은 가장 선행되어야 하는 연구 분야 중 하나이다. RADAR (RAdio Detection And Ranging) 및 AIS (Automatic Identification System) 등의 전통적인 인지 센서를 활용한 연구가 진행 중이지만 사각지대나 탐지 주기 등의 한계가 있다. 따라서 본 연구에서는 다중 카메라 (광학, 열상, 파노라마)를 이용하여 전통적인 인지 센서의 한계를 보완하는 새로운 인지 시스템을 고안하였으며, 이를 기반으로 해상 장애물을 추적하여 동적 운동 정보를 얻었다. 먼저 실해역에서 수집한 이미지를 바탕으로 해상 장애물 탐지를 위한 데이터를 구성하고, 딥 러닝 기반의 탐지 모델을 학습시켰다. 탐지 모델을 이용하여 탐지한 결과는 직접 설계한 칼만 필터 기반의 적응형 추적 필터를 통과시켜 해상 장애물의운동 정보 (궤적, 속력, 방향)를 계산하는데 활용되었다. 또한 본 연구는 카메라를 센서로 활용했을 때의 한계를 보완하기 위하여 동 시간대에 다중 카메라에서 추적한 각각의 정보를 융합하였다. 그 결과 단일 카메라를 활용하는 경우, RADAR의 오차 범위 이내에 추적 결과가 수렴하는 양상을 보였으며, 다중 카메라를 활용하는 경우에는 단일 카메라보다 정확한 추적이 가능함을 확인하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.133-140
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• 2016

In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.411-422
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• 2021

The autonomous driving system mounted on the unmanned vehicle recognizes the external environment through several sensors and derives the optimum control value through it. Recently, studies on physical level attacks that maliciously manipulate sensor data by performing signal-injection attacks have been published. signal-injection attacks are performed at the physical level and are difficult to detect at the software level because the sensor measures erroneous data by applying physical manipulations to the surrounding environment. In order to detect a signal-injection attack, it is necessary to verify the dependability of the data measured by the sensor. As so far, various methods have been proposed to attempt physical level attacks against sensors mounted on autonomous driving systems. However, it is still insufficient that methods for defending and detecting the physical level attacks. In this paper, we demonstrate signal-injection attacks targeting MEMS sensors that are widely used in unmanned vehicles, and propose a method to detect the attack. We present a signal-injection detection model to analyze the accuracy of the proposed method, and verify its effectiveness in a laboratory environment.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.17-26
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• 2021

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.262-265
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• 2008

수천 개의 센서 노드들 간의 공동 작업을 기반으로 한 무선 센서 네트워크는 대규모 서식지 모니터링, 침입 탐지, 자동화된 실시간 위치 평가, 홈 어플리케이션, 과학적인 탐사 등 수많은 응용에 대한 새로운 플랫폼을 제공하고 있다. 본 논문은 수천 개의 센서노드들이 센서 필드에 전개되어 있는 경우에 센서 노드의 상태를 효율적으로 관리하기 위해 센서 노드의 위치를 탐지하기 위한 방법에 관하여 기술하였다. 기본적으로 PEGASIS 라우팅 알고리즘을 이용하여 노드들 간의 상대 거리 정보를 수집하여 센서 노드의 위치 정보를 탐지하였다.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.51-57
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• 2017

A wireless sensor network is composed of many resource constrained sensor nodes. These networks are attacked by malicious attacks like DDoS and routing attacks. In this paper, we propose the intrusion detection and prevention system using convergence of software-defined networking and security technology in wireless sensor networks. Our proposed scheme detects various intrusions in a central server by accumulating log messages of OpenFlow switch through SDN controller and prevents the intrusions by configuring OpenFlow switch. In order to validate our proposed scheme, we show it can detect and prevent some malicious attacks in wireless sensor networks.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.289-290
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• 2022

본 연구에서는 선박의 중요부품인 메인엔진에서 수집되는 센서 데이터를 사용하여 선박 메인엔진의 이상치를 탐지하는 시스템을 소개한다. 본 시스템의 특장점은 이상치 탐지 뿐만 아니라, 이상치의 센서별 기여도를 정량화 함으로써, 이상치 발생을 유형화 하고 추가적인 분석을 가능하게 해준다. 또한 웹 인터페이스 형태의 편리한 UI를 개발하여 사용자들이 보다 편리하게 이상치

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.188-190
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• 2008

본 논문에서는 초음파 센서를 이용하여 이동하는 표적의 위치를 실시간으로 추적하는 위치추적 시스템을 개발하였다. 위치 추적 시스템은 4 개의 초음파 센서를 이용해서 각 센서에서 탐지되는 표적까지의 거리 정보를 이용하여 이동하는 표적의 위치좌표(x,y)를 구하였다. 특히 초음파 센서가 가지고 있는 빔폭 특성을 고려하여 4 개 센서 중 2개 센서에만 표적이 탐지될 경우 표적의 위치를 최적화하는 방안을 제시하였으며 개발된 알고리즘을 하드웨어에 장착하어 감시시스템이 실시간 양호하게 구동하는것을 확인하였다.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.507-516
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• 2001

In this paper, we implement sequence-based anomaly detection sensor using SOM and HMM, and analyze what is important information in system call and how a threshold is decided. The new filtering and reduction rules of SOM reduces the input size of HMM. This gives real-time processing to HMM-based anomaly detection sensor. Also, we introduced an anomaly count into the sensor. Due to lessened sensibility, a user easily understand easily the detection information and false-positive was decreased. And the active coordination of the threshold value makes the detection sensor adapt according to the system condition.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.5
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• pp.499-507
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• 2004

We have studied tile detection techniques, which can determine the location and the weight of an intruder into infrastructure, by using fiber-optic ROTDR (Rayleigh optical time domain reflectometry) sensor and fiber-optic BOTDA (Brillouin Optical time domain analysis) sensor, which can use an optical fiber longer than that of ROTDR sensor Fiber-optic sensing plates of ROTDR sensor, which arc buried in sand, were prepared to respond the intruder effects. The signal of ROTDR was analyzed to confirm the detection performance. The constructed ROTDR could be used up to 10km at the pulse width of 30ns. The location error was less than 2 m and the weight could be detected as 4 grades, such as 20kgf, 40kgf, 60kgf and 80kgf. Also, fiber optic BOTDA sensor was developed to be able to detect intrusion effect through an optical fiber of tells of kilometers longer than ROTDR sensor. fiber-optic BOTDA sensor was constructed with 1 laser diode and 2 electro-optic modulators. The intrusion detection experiment was peformed by the strain inducing set-up installed on an optical table to simulate all intrusion effect. In the result of this experiment, the intrusion effort was well detected as the distance resolution of 3m through the fiber length of about 4.81km during 1.5 seconds.