• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.661-663
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• 2001

침입탐지 시스템은 내부자의 불법적인 사용, 오용 또는 외부 침입자에 의한 중요 정보 유출 및 변경을 알아내는 것으로서 각 운영체제에서 사용자가 발생시킨 키워드, 시스템 호출, 시스템 로그, 사용시간, 네트워크 패킷 등의 분석을 통하여 침입여부를 결정한다. 본 논문에서 제안하는 침입탐지시스템은 권한 이동 관련 이벤트 추출 기법을 이용하여 사용자의 권한이 바뀌는 일정한 시점만큼 기록을 한 후 HMM모델에 적용시켜 평가한다. 기존 실험에서 보여주었던 데이터의 신뢰에 대한 단점을 보완하기 위해 다량의 정상행위 데이터와 많은 종류의 침입유형을 적용해 보았고, 그 밖에 몇 가지 단점들을 수정하여 기존 모델에 비해 향상된 성능을 보이는지를 평가하였다 실험 결과 호스트기반의 침입에 대해서 매우 좋은 탐지율을 보여 주었고 F-P error(false positive error) 또한 매우 낮은 수치를 보여 주었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.53-56
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• 2007

CAD와 같이 계산위주의 응용을 지원하기 위해 개발된 초기의 객체지향 데이터베이스 시스템은 클라이언트에서 자료의 요구와 처리를 허용하는 자료 탑재방식이다. 이 방식은 클라이언트 워크스테이션에서 수행되는 작업의 대부분을 수행할 수 있는 지역 DBMS를 허용한다. 클라이언트 워크스테이션에서 자료와 잠금을 캐싱하는 것은 클라이언트-서버 데이터베이스 시스템의 성능 향상을 위한 중요한 기술이다. 이 논문에서는 클라이언트 워크스테이션이 자신의 지역 데이터베이스를 유지하면서 회피 또는 탐지 기반의 캐시일관성 유지 알고리즘들의 성능을 평가할 수 있도록 하는 클라이언트 워크스테이션을 모델링하고 구현하였다. 이 시스템은 3개의 클라이언트로 구성되고, 각 지역 동시성 제어 기법으로는 2PL을 사용하였다. 이 모델은 멀티데이터베이스 시스템 환경으로 확장 가능하다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.407-417
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• 2019

When a free-falling ballistic missile intercepts a maritime target in a sea clutter environment at high grazing angle, detection performance of the ballistic missile's seeker can be rapidly degraded by the effect of sea clutter. To solve this problem, it is necessary to verify the performance of maritime target detection via simulations based on various scenarios. We accomplish this by applying a two-dimensional cell -averaging constant false alarm rate detector to a two-dimensional radar image, which is generated by merging a sea clutter signal at high grazing angle with a maritime target signal corresponding to the signal-to-clutter ratio. Simulation results using a computer-aided design model and commercial numerical electromagnetic solver in various scenarios show that the performance of maritime target detection significantly depends on the grazing and azimuth angles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.208-218
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• 2006

In this paper, we introduce the creation methods of attack detection model using data mining technologies that can classify the latest attack types, and can detect the modification of existing attacks as well as the novel attacks. Also, we evaluate comparatively these attack detection models in the view of detection accuracy and detection time. As the important factors for creating detection models, there are data, attribute, and detection algorithm. Thus, we used NetFlow data gathered at the real network, and KDD Cup 1999 data for the experiment in large quantities. And for attribute selection, we used a heuristic method and a theoretical method using decision tree algorithm. We evaluate comparatively detection models using a single supervised/unsupervised data mining approach and a combined supervised data mining approach. As a result, although a combined supervised data mining approach required more modeling time, it had better detection rate. All models using data mining techniques could detect the attacks within 1 second, thus these approaches could prove the real-time detection. Also, our experimental results for anomaly detection showed that our approaches provided the detection possibility for novel attack, and especially SOM model provided the additional information about existing attack that is similar to novel attack.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.443-451
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• 2015

This paper proposes a signal modelling method that can effectively detect the shock wave(SW) sound and muzzle blast(MB) sound from the gunshot of a small arm rifle. In order to localize a counter sniper in battlefield, an accurate detection of both shock wave sound and muzzle blast sound are the necessary keys in estimating the direction and the distance of the counter sniper. To verify the performance of the proposed algorithm, a real gunshot sound in a domestic military shooting range was recorded and analyzed. From the experimental results, the proposed signal modelling method was found to be superior to the comparative system more than 20% in a shock wave detection and 5% in a muzzle blast detection, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.10
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• pp.1045-1052
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• 2015

In this paper, a stabilized control algorithm for the large rotating stand of a long-range surveillance radar (LRSR) system is introduced. The stabilized control algorithm for this large rotating stand system was designed using mathematical plant modeling. The LRSR system is located on high ground and has a wide surface, making it susceptible to the effects of wind, which increases the bearing friction and reduces the stability of the rotating stand. The disturbance caused by the wind was analyzed using computational fluid dynamics (CFD) in this study. The results of the CFD analysis were used to construct a control algorithm for the disturbance . The performance of the proposed control algorithm was demonstrated experimentally and through simulations. The plant model and the control algorithm were constructed in Matlab/Simulink.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.83-90
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• 2008

We introduce the coordination among the intrusion detection agents by BBA(BlackBoard Architecture) that belongs to the field of distributed artificial intelligence. The system which uses BBA for the coordination can be easily expanded by adding new agents and increasing the number of BB(BlackBoard) levels. Several simulation tests performed on the targer network will illustrate our techniques. And this paper applies PBN(Policy-Based Network) to reduce the false positives that is one of the main problems of IDS. The performance obtained from the coordination of intrusion detection agent with PBN is compared against the corresponding non PBN type intrusion detection agent. The application of the research results lies in the experimentation of the various security policies according to the network types in selecting the best security policy that is most suitable for a given network.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.125-133
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• 2009

RDF is widely used as the ontology language for representing metadata on the semantic web. Since ontology models the real-world, ontology changes overtime. Thus, it is very important to detect and analyze changes in knowledge base system. Earlier studies on detecting changes between RDF models focused on the structural differences. Some techniques which reduce the size of the delta by considering the RDFS entailment rules have been introduced. However, inferencing with RDF models increases data size and upload time. In this paper, we propose a new change detection using RDF reasoning that only computes a small part of the implied triples using backward chaining strategy. We show that our approach efficiently detects changes through experiments with real-life RDF datasets.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2007.04a
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• pp.245-249
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.

• Journal of the Korean Society of Propulsion Engineers
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• v.11 no.3
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• pp.29-34
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• 2007

In this study a model-based diagnostic method using the Neural Network was proposed for PW206C turbo shaft engine and performance model was developed by SIMULINK. Fault and test database to build the NN was obtained at various off-design operating range such as flight altitude, flight Mach number and gas generator rotational speed variation. According to the fault detection analysis results, it was confirmed that the proposed fault detection method could find well the fault of compressor, compressor turbine and power turbine at on-design point as well as off-design point conditions.