• Journal of IKEEE
• /
• v.12 no.3
• /
• pp.158-166
• /
• 2008

Medical ultrasound has benefits in mobility and safety than any other medical techniques such as X-ray, CT and MRI but has speckle noise which decrease the ability of an observer to distinguish the fine details in diagnostic examination. But simple removing of speckle often causes losing boundary information. Then, in this paper, we presented a novel neuro-fuzzy method which could remove speckle efficiently without loss of boundary information. Proposed method consists of image clustering by fuzzy algorithm and image processingby neural networks which was learned by back propagation. From the experiments for simulation image and real ultrasound image, we could verify the proposed method.

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.53-61
• /
• 2010

In wireless sensor networks(WSNs) individual sensor nodes are subject to security compromises. An adversary can physically capture sensor nodes and obtain the security information. And the adversary injects false reports into the network using compromised nodes. If undetected, these false reports are forwarded to the base station. False reports injection attacks can not only result in false alarms but also depletion of the limited amount of energy in battery powered sensor nodes. To combat these false reports injection attacks, several filtering schemes have been proposed. The statistical en-routing filtering(SEF) scheme can detect and drop false reports during the forwarding process. In SEF, The number of the message authentication codes(threshold) is important for detecting false reports and saving energy. In this paper, we propose a dynamic threshold determination method for energy efficient SEF using fuzzy-logic in wireless sensor networks. The proposed method consider false reports rate and the number of compromised partitions. If low rate of false reports in the networks, the threshold should low. If high rate of false reports in networks, the threshold should high. We evaluated the proposed method’s performance via simulation.

• Journal of the Korea Society for Simulation
• /
• v.15 no.4
• /
• pp.29-39
• /
• 2006

Sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. A number of routing protocols to transmit the data between the base station and sensor nodes have been proposed. Intanagonwiwat et al. proposed the directed diffusion in which the base station sends interest messages and waits for data from the nodes in the specific regions. Since the directed diffusion propagates every interest message to whole nodes in the network, it causes energy dissipation of nodes. In this paper, we propose a novel data propagation method, which limits the data transmission area according to a threshold value for reducing the energy consumption in the network. A fuzzy logic is exploited to determine the threshold value by considering the energy and density of all the deployed nodes. The simulation models are designed and implemented based on DEVS formalism which is theoretically well grounded means of expressing discrete event simulation models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.340-343
• /
• 2006

본 논문은 스마트 홈에서 베이지안 네트워크에 기반을 둔 보편성을 가지는 상황인식 시스템의 구현방법을 제안한다. 상호정보를 사용하여 베이지안 네트워크의 구조 학습을 하고, 보다 효율적인 데이터 처리를 위해서 퍼지 클러스터링을 사용하는 방법을 도입한다. 마지막으로 시뮬레이터를 통하여 자료 취득 및 상황인식의 결과를 보인다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10a
• /
• pp.72-73
• /
• 2007

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.77-80
• /
• 2007

현재 생명공학은 급속도로 발전하고 있으며, 이를 통해 만들어지는 생물정보의 양은 기하급수적으로 늘어나고 있다. 이러한 것을 가능하게 하는 기술 중의 하나인 마이크로어레이 기법은 현재 질병의 진단 및 신약 개발 등을 위해 사용되고 있다. 마이크로어레이 유전자 발현에 관한 분석은 크게 유의한 유전자 추출, 클러스터링, 분류 및 유전자 네트워크 구축 등으로 볼 수 있다. 유의한 유전자 식별을 위한 통계학적 방법으로 T-test 및 Wilcoxon Rank Sum test 등이 있다. 최근에는 수정인자를 추가하거나 혹은 퍼지이론 등의 지능정보 이론을 추가하여 그 계산결과를 좀 더 상세화하고 세분화하는 연구들이 계속되고 있다. 본 논문에서는 두 개의 그룹에서 발현된 유전자들 중 유의하게 발현되는 유전자를 식별하기 위한 방법으로 퍼지이론을 도입하여 유의한 유전자를 규명하는 FST(Fuzzy Significance Test) 방법을 제안한다.

• Journal of Korean Society of Transportation
• /
• v.23 no.8 s.86
• /
• pp.171-179
• /
• 2005

This paper presents the algorithm using fuzzy inference that preestimates each link speed changed by different kinds of road situations. The elements we are considered are time zone, rainfall probability information and lane control information. This paper is consists of three parts. First of all we set up the fuzzy variables, and preestimate link speed changed by various road situations. For this process, we build the membership functions for each fuzzy variable and establish the fuzzy inference relations to find how fuzzy variables influence on link speed. Second, using backtracking method, we search the shortest route influenced by link speed changed by fuzzy inference. Third, we apply this algorithm to hypothetical network and find the shortest path. As a result, it is shown that this algorithm choose appropriate roundabout path according to the changing road situations.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.1017-1020
• /
• 2007

컴퓨터의 생활 전반에 걸친 영향으로, 컴퓨터는 우리 생활 속에서 빼놓을 수 없는 하나의 정보 매체로 자리 매김 되었다. 하지만 그 이면에는 컴퓨터를 이용한 전산망 침해 행위, 전자기록 위.변조, 각종 음란물 유통, 바이러스 제작 유포 등 많은 위험들이 우리를 위협하고 있다. 그래서 컴퓨터를 사용한 범죄 행위를 탐지하는 방법에 대한 관심이 높아지고 있다. 또한 각종 범죄 행위는 인터넷을 통한 범죄가 늘고 있어, 네트워크 정보를 통한 포렌식에 관한 연구가 활발하다. 하지만, 매일 많은 양의 패킷을 분석하는 것은 많은 전문 인력과 비용이 소요된다. 본 논문에서는 의사결정나무를 이용한 패킷분석을 통하여 네트워크 포렌식의 정보를 추출하는 방법을 제안한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2002.12a
• /
• pp.258-261
• /
• 2002

최근 네트워크 취약점 검색 방법을 이용한 침입 공격이 증가하는 추세이며 이런 공격에 대하여 적절하게 실시간 탐지 및 대응 처리하는 침입방지시스템(IPS: Intrusion Prevention System)에 대한 연구가 지속적으로 이루어지고 있다. 본 논문에서는 시스템에 허락을 얻지 않은 서비스거부 공격(Denial of Service Attack) 기술 중 TCP의 신뢰성 및 연결 지향적 전송서비스로 종단간에 이루어지는 3-Way Handshake를 이용한 Syn Flooding Attack에 대하여 침입시도패킷 정보를 수집, 분석하고 퍼지인식도(FCM : Fuzzy Cognitive Maps)를 이용한 침입시도여부결정 및 대응 처리하는 네트워크 기반의 실시간 탐지 및 방지 모델(Network based Real Time Scan Detection & Prevention Model)을 제안한다.

• Journal of the Korea Society for Simulation
• /
• v.16 no.2
• /
• pp.27-35
• /
• 2007

When sensor networks are deployed in open environments, all the sensor nodes are vulnerable to physical threat. An attacker can physically capture a sensor node and obtain the security information including the keys used for data authentication. An attacker can easily inject false reports into the sensor network through the compromised node. False report can lead to not only false alarms but also the depletion of limited energy resource in battery powered sensor networks. To overcome this threat, Fan Ye et al. proposed that statistical on-route filtering scheme(SEF) can do verify the false report during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and energy, where security threshold value is the number of message authentication code for verification of false report. In this paper, we propose a fuzzy rule-based system for security threshold determination that can conserve energy, while it provides sufficient detection power in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the probability of a node having non-compromised keys, the number of compromised partitions, and the remaining energy of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.