• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.431-434
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• 2014

웹서비스 사용이 보편화되면서 웹 애플리케이션의 보안취약점을 악용하는 해커들이 늘어나고 있다. 악의적인 공격으로 인한 피해를 막기 위해 보안을 견고하게 하지만 보안취약점에 의한 피해가 빈번하게 발생하고 있다. 본 논문에서는 이러한 보안취약점 중 SQL Injection 취약점과 NoSQL Injection 취약점을 분석하고, 침투 시험을 통해 사용자의 최소한의 개입만으로 SQL Injection 취약점과 NoSQL Injection 취약점을 자동으로 탐지하는 도구의 설계 방법을 제안한다. 제안한 도구는 SQL Injection 취약점과 NoSQL Injection 취약점을 탐지하기 위한 전문적인 보안 지식을 요구하지 않기 때문에 자동 침투 시험 도구를 사용하면 보안 비전문가도 쉽게 취약점을 탐지할 수 있다.

• Journal of IKEEE
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• v.26 no.4
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• pp.622-627
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• 2022

This paper proposes an intrusion detection system for in-vehicle network to improve detection performance considering attack counts and attack types. In intrusion detection system, both FNR (False Negative Rate), where intrusion frame is misjudged as normal frame, and FPR (False Positive Rate), where normal frame is misjudged as intrusion frame, seriously affect vechicle safety. This paper proposes a novel intrusion detection algorithm to improve both FNR and FPR, where data frame previously detected as intrusion above certain attack counts is automatically detected as intrusion and the automatic intrusion detection method is adaptively applied according to attack types. From the simulation results, the propsoed method effectively improve both FNR and FPR in DoS(Denial of Service) attack and spoofing attack.

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.78-83
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• 2000

Passive sonar system is designed to classify the underwater targets by analyzing and comparing the various acoustic characteristics such as signal strength, bandwidth, number of tonals and relationship of tonals from the extracted tonals and frequency lines. First of all the precise detection and extraction of signal frequency lines is of particular importance for enhancing the reliability of target classification. But, the narrowband frequency lines which are the line formed in spectrogram by a tonal of constant frequency in each frame can be detected weakly or discontinuously because of the variation of signal strength and transmission loss in the sea. Also, it is very difficult to detect and extract precisely the signal frequency lines by the complexity of impulsive ambient noise and signal components. In this paper, the automatic detection and extraction method that can detect and extract the signal components of frequency tines precisely are proposed. The proposed method can be applied under the bad conditions with weak signal strength and high ambient noise. It is confirmed by the simulation using real underwater target data.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.522-529
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• 2018

FOD refers to various metals and non-metallic foreign substances that pose a risk to aircraft. FODs occur in all areas and time zones, including runways, taxiways, and maintenance facilities, and pose a fatal hazard to aircraft safety during aircraft movements and take-off and landing. Rapid and effective detection and removal of FODs in the runway is required. As part of recent developments in aviation safety technologies, automatic detection of debris in runways in airports is under way. In this paper, we conducted an automated detection test using the EO/IR camera and radar at the Taean campus of Hansu University to confirm normal detection during the day and night.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.601-603
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• 2002

공유메모리 병렬프로그램에서 경합은 프로그램의 비결정적인 수행을 초래하므로 디버깅을 위해서 반드시 탐지되어져야 한다. 경합을 수행 중에 디버깅하기 위한 기존의 도구들은 경합탐지 엔진과 시각화 엔진으로 구성된 경합디버깅 엔진을 특정 프로그램 모델에 의존적으로 적용하여 경합디버깅 환경을 구성한다. 이러한 도구들은 프로그램 모델의 변경 시에 경합디버깅 환경이 최적의 경합 디버깅 엔진으로 구성되지 못한다는 문제점이 있다. 본 논문에서는 OpenMP 병렬프로그랭에서 각 프로그램 모델에 따라 효과성, 효율성, 확장성 등을 고려한 경합탐지 엔진과 추상성을 고려한 시각화 엔진으로 경합디버깅 환경을 자동으로 생성하는 도구를 제안한다. 이 도구는 디버깅 대상이 되는 프로그램의 모델에 최적인 경합디버깅 엔진을 적용하므로 경합탐지 목적에 부합하는 최적의 성능과 효과적인 시각화를 제공한다. 따라서, 본 도구는 디버깅 환경을 생성하기 위한 부담을 줄여서 효과적인 디버깅을 할 수 있게 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.365-367
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• 2014

최근 웹 서비스의 증가와 악성코드는 그 수를 판단 할 수 없을 정도로 빠르게 늘어나고 있다. 매년 늘어나는 악성코드는 금전적 이윤 추구가 악성코드의 주된 동기가 되고 있으며 이는 공공기관 및 보안 업체에서도 악성코드를 탐지하기 위한 연구가 활발히 진행되고 있다. 본 논문에서는 실시간으로 패킷을 분석할수 있는 필터링과 웹 크롤링을 통해 도메인 및 하위 URL까지 자동적으로 탐지할 수 있는 악성코드 탐지 시스템을 제안한다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.118-124
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• 1996

Signal frequency lines generated from the acoustic targets are of particular importance for target detection and classification in passive sonar systems. The underwater noise consists of a mixture of ambient noise and radiated noise of targets. Detction of exact signal frequency lines depends on signal detection threshold and variation of ambient noise. In this paper, a detection method of signal frequency lines for acoustic targets using autoassociative memory (ASM) neural network, which is not sensitive to variation of signal detection threshold and ambient noise, is proposed. It is confirmed by simulation and application of real acoustic targets that the proposed method shows good performance for detection of signal frequency lines.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.227-243
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• 2008

This study investigates an event detection method with the aim of generating an event-focused news summary from a set of news articles on a certain event using a multi-document summarization technique. The event detection method first classifies news articles into the event related topic categories by employing a SVM classifier and then creates event clusters containing news articles on an event by a modified single pass clustering algorithm. The clustering algorithm applies a time penalty function as well as cluster partitioning to enhance the clustering performance. It was found that the event detection method proposed in this study showed a satisfactory performance in terms of both the F-measure and the detection cost.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.565-567
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• 2004

All IP,NGN(Next Generation Network)으로 대변되는 차세대 네트워크의 특징 중 하나는 이동성이며 노드의 이동뿐만 아니라 네트워크 전체가 이동하는 모바일 네트워크로 진화하고 있다. 차세대 네트워크의 하위 구조를 이루게 될 MANET에 IPv6를 적용하기 위해, 보다 확장성 있고, 유연하며. 빠르고 가벼운 IPv6의 자동 주소 지정 및 중복 주소 탐지에 관해 논의한다.