• Convergence Security Journal
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• v.23 no.2
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• pp.37-45
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• 2023

Cyber deception technology plays a crucial role in monitoring attacker activities and detecting new types of attacks. However, along with the advancements in deception technology, the development of Anti-honeypot technology has allowed attackers who recognize the deceptive environment to either cease their activities or exploit the environment in reverse. Currently, deception technology is unable to identify or respond to such situations. In this study, we propose a predictive model using Markov chain analysis to determine the identification of attackers who infiltrate deceptive environments. The proposed model for deception status determination is the first attempt of its kind and is expected to overcome the limitations of existing deception-based attacker analysis, which does not consider attackers who identify the deceptive environment. The classification model proposed in this study demonstrated a high accuracy rate of 97.5% in identifying and categorizing attackers operating in deceptive environments. By predicting the identification of an attacker's deceptive environment, it is anticipated that this model can provide refined data for numerous studies analyzing deceptive environment intrusions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.311-317
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• 2009

The traditional network anomaly detection systems execute the threshold-based detection without considering dynamic network environments, which causes false positive and limits an effective resource utilization. To overcome the drawbacks, we present the adaptive network anomaly detection model based on artificial immune system (AIS) in centralized network. AIS is inspired from human immune system that has learning, adaptation and memory. In our proposed model, the interaction between dendritic cell and T-cell of human immune system is adopted. We design the main components, such as central node and router node, and define functions of them. The central node analyzes the anomaly information received from the related router nodes, decides response policy and sends the policy to corresponding nodes. The router node consists of detector module and responder module. The detector module perceives the anomaly depending on learning data and the responder module settles the anomaly according to the policy received from central node. Finally we evaluate the possibility of the proposed detection model through simulation.

• The Journal of Bigdata
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• v.7 no.1
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• pp.89-97
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• 2022

Various efforts are needed to prevent accidents because ship collisions can cause various negative situations such as economic losses and casualties. Therefore, research to prevent accidents is being actively conducted, and in this study, new leading indicators for preventing ship collision accidents is proposed. In previous studies, the risk of collision was expressed in consideration of the distance between ships in a specific sea area, but there is a disadvantage that a new model needs to be developed to apply this to other sea areas. In this study, the density-based ship domain DESD (Density-based Empirical Ship Domain) including the environment and operating characteristics of the sea area was defined using AIS (Automatic Identification System) data, which is ship operation information. Deep clustering is applied to two-dimensional DESDs created for each sea area to cluster the seas with similar operating environments. Through the analysis of the relationship between clustered sea areas and ship collision accidents, it was statistically tested that the occurrence of accidents varies by characteristic of each sea area, and it was proved that DESD can be used as a leading indicator of accidents.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.8-10
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• 2017

최근 빈번한 항해 사고에 대응하여 항해 안전에 대한 관심이 높아지고 있으며 특히 항해중인 선박의 안전 항해에 대한 육상 감시기술 개발에 많은 노력이 기울려 지고 있다. 이러한 육상용 항해안전 감시시스템은 항만 교통 번잡도에 따른 조종 위험성 평가 기능 및 해양기상에 따른 선박 안전성능 평가 기능 등으로 구성되며, 선박 안전성능 평가를 위하여 선박에서 전송되는 AIS정보를 운항정보로 변환하여 구축된 선박별 동특성 정보와 연결한 후 안전성능지수를 도출하는 기술 구현이 필요하다. 본 연구에서는 이러한 항해안전 감시시스템 개발을 위하여 환경 요인에 의한 항해중 선박의 위험 요소를 분석, 항해안전 평가 모델을 개발한 후 개발된 평가 모델에 대한 평가 기준을 제시하였고 각 평가 모델의 결과를 정량적 지수형태로 도출하여 안전항해 감시시스템의 정량적 평가 기능을 지원하였다.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.141-144
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• 2009

The purpose of this study is to develop the auxiliary rehabilitation device for a patient of spinal curvature. The adolescent diopathic scoliosis(AIS) must be treated by rehabilitation brace if Cobb angle is $20^{\circ}{\sim}40^{\circ}$. The rehabilitation brace is consist of 4 vest and 2 hinge parts(hinge and couple bar) that give a force to the ribs. But thin and light hinge parts for young patient failed easily because of unusual movement of the upper body. We studied optimum design and structural analysis of hinge parts when it distorted by tensile and bending force. The specimen of hinge parts were tested to evaluate the failure strength. And we attached circuits with memory and sensor detecting pressure and displacement to recoding stress in hinge parts. These data are used to alarm the patient to stop unusual movement and understand the load history.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.77-82
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• 2006

Automatic vessel collision-avoidance systems have been studied in the fields of artificial intelligence and navigation for decades. And to facilitate automatic collision-avoidance decision-making in two-vessel-encounter situation, several expert and fuzzy expert systems have been developed. However, none of them can negotiate with each other as seafarers usually do when they intend to make a more economic overall plan of collision avoidance in the COLREGS-COST-HIGH situations where collision avoidance following the International Regulations for Preventing Collisions at Sea(COLREGS) costs too much. Automatic Identification System(AIS) makes data communication between two vessels possible, and negotiation methods can be used to optimize vessel collision avoidance. In this paper, a negotiation framework is put forward to enable vessels to negotiate to optimize collision avoidance in the COLREGS-COST-HIGH situations at open sea. A vessel vector space is defined and therewith a cost model is put forward to evaluate the cost of collision-avoidance actions. Negotiations between a give-way vessel and a stand-on vessel and between two give-way vessels are considered respectively to reach overall low cost agreements. With the framework proposed in this paper, two vessels involved in a COLREGS-COST-HIGH situation can negotiate with each other to get a more economic overall plan of collision avoidance than that suggested by the traditional collision-avoidance expert systems.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.146-154
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• 2023

Efforts have been made to reduce the greenhouse gas emissions from ships by limiting the energy efficiency index, and net zero CO₂ emission was proposed recently. The most ideal measure to achieve zero emission ship is electrification, and fuel cells are considered as a practical power source of the electrified propulsion system. The electric efficiency in the electrochemical reaction of fuel cells can be achieved up to 60% practically. The remaining energy is converted to heat energy but most of them are dissipated by cooling. In the author's previous research, a hybrid propulsion system utilizing not only electricity but also heat was introduced by combining electric motor and steam turbine. In this article, long term efficiency is evaluated for the introduced hybrid propulsion system by considering a virtual 24,000 TEU class container carrier model. To reflect a more practical operating condition, the actual navigation data of a similar real ship in the real world were collected from automatic identification system data and applied. From the result, the overall efficiency of the hybrid propulsion system is expected to be higher than a conventional electric propulsion fuel cell ship by 30%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.47-56
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• 2010

In navigation, officers receive data about inside and outside of ship from several devices(ex, GPS / AIS / ECDIS / ARPA Radar / etc) in bridge, and use it to recognize and predict safety situations. However, observation work of a officer is still hard for a torrent of data from several devices, and the problem of inconsistent data among the devices. In previous research, we presented the conceptual model of Intelligent Navigation Safety Information System based on information fusion, and showed the example of the conceptual model using CF (Certainty Factor) expert system to solve this problem. The information fusion technology needs various reasoning skills, and CF expert system is not enough to express ambiguous or indefinite factors. In this paper, we propose the concept of an intelligent navigation information fusion using fuzzy expert system to describe the ambiguous factors, and show the validity of applying fuzzy expert system to the Navigation Safety Information System through the design and implementation of the proposed concept.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.119-130
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• 2010

The Genetic Algorithm has been frequently applied by many researchers as one of the population surface modelling tool in estimating the regional population based on the gridded spatial system. Taking the East-Hwasung area as the case, this study first builds a gridded population data based on the KLIS and eAIS databases as well as municipal population survey data, and then constructs the attribute values of the explanatory variables by way of GIS tools. The GA model is run to maximize its fitness function measuring the correlation coefficient between the observed and predicted values of the 70 population cells. It is shown that the GA output predicted reasonably consistent and meaningful coefficient estimates for the explanatory variables of the model.