• 한국산학기술학회논문지
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• 제11권7호
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• pp.2528-2533
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• 2010

본 논문은 대방미사일(ARM: Anti Radiation Missile)로부터 레이다를 보호하기 위한 전파회피기술의 분석에 사용될 시뮬레이터 개발에 관한 것이다. 제시된 시뮬레이터는 전파회피를 위해 널리 사용되는 디코이(Decoy) 안테나의 효과적인 배치와 ARM 수신기에 수신되는 전파의 특성 분석이 가능하다. 그리고 디코이 안테나의 배치 효과를 검증하기위해 ARM 수신기에 도달하는 디코이 안테나 신호의 위상과 진폭을 분석하였다. 또한 다수 디코이 안테나를 사용하는 경우 ARM의 공격효과를 다양하게 분석하였으며 제안된 시뮬레이터는 ARM 방어를 위한 효과적인 디코이 배치에 유용하게 활용 될 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권9호
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• pp.2982-3003
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• 2014

With the explosive deployment of the wireless communications technology, the increased QoS requirement has sparked keen interest in network planning and optimization. As the major players in wireless network optimization, the BS's resource utilization and mobile user's QoS can be improved a lot by the load-balancing technology. In this paper, we propose a load-balancing strategy that uses Coordinated Multiple Points (CoMP) technology among the Base Stations (BS) to effectively extend network coverage and increase edge users signal quality. To use universally, different patterns of load-balancing based on CoMP are modeled and discussed. We define two QoS metrics to be guaranteed during CoMP load balancing: call blocking rate and efficient throughput. The closed-form expressions for these two QoS metrics are derived. The load-balancing capacity and QoS performances with different CoMP patterns are evaluated and analyzed in low-dense and high-dense traffic system. The numerical results present the reasonable CoMP load balancing pattern choice with guaranteed QoS in each system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4703-4723
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• 2016

The verification of data integrity is an urgent topic in remote data storage environments with the wide deployment of cloud data storage services. Many traditional verification algorithms focus on the block-oriented verification to resolve the dispute of dynamic data integrity between the data owners and the storage service providers. However, these algorithms scarcely pay attention to the data verification charge and the users' verification experience. The users more concern about the availability of accessed files rather than data blocks. Moreover, the data verification charge limits the number of checked data in each verification. Therefore, we propose a mixed verification protocol to verify the data integrity, which rapidly locates the corrupted files by the file-oriented verification, and then identifies the corrupted blocks in these files by the block-oriented verification. Theoretical analysis and simulation results demonstrate that the protocol reduces the cost of the metadata computation and transmission relative to the traditional block-oriented verification at the expense of little cost of additional file-oriented metadata computation and storage at the data owner. Both the opportunity of data extracted and the scope of suspicious data are optimized to improve the verification efficiency under the same verification cost.

• Nuclear Engineering and Technology
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• 제49권5호
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• pp.896-904
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• 2017

Several Generation IV nuclear reactor concepts have goals for optimizing investment recovery through phased introduction of multiple units on a common site with shared facilities and/or reconfigurable energy conversion systems. Additionally, small modular reactors are suitable for remote deployment to support highly localized microgrids in isolated, underdeveloped regions. The long-term economic viability of these advanced reactor plants depends on significant reductions in plant operations and maintenance costs. To accomplish these goals, intelligent control and diagnostic capabilities are needed to provide nearly autonomous operations with anticipatory maintenance. A nearly autonomous control system should enable automatic operation of a nuclear power plant while adapting to equipment faults and other upsets. It needs to have many intelligent capabilities, such as diagnosis, simulation, analysis, planning, reconfigurability, self-validation, and decision. These capabilities have been the subject of research for many years, but an autonomous control system for nuclear power generation remains as-yet an unrealized goal. This article describes a functional framework for intelligent, autonomous control that can facilitate the integration of control, diagnostic, and decision-making capabilities to satisfy the operational and performance goals of power plants based on multimodular advanced reactors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권7호
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• pp.3369-3385
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• 2019

There are various research challenges in vehicular ad hoc networks (VANETs) that need to be focused until an extensive deployment of it becomes conceivable. Design and development of a scalable routing algorithm for VANETs is one of the critical issue due to frequent path disruptions caused by the vehicle's mobility. This study aims to provide a novel road-aware routing protocol for vehicular networks named as Two-level hierarchical Hybrid Road-Aware (THERA) routing for vehicular ad hoc networks. The proposed protocol is designed explicitly for inter-vehicle communication. In THERA, roads are distributed into non-overlapping road segments to reduce the routing overhead. Unlike other protocols, discovery process does not flood the network with packet broadcasts. Instead, THERA uses the concept of Gateway Vehicles (GV) for the discovery process. In addition, a route between source and destination is flexible to changing topology, as THERA only requires road segment ID and destination ID for the communication. Furthermore, Road-Aware routing reduces the traffic congestion, bypasses the single point of failure, and facilitates the network management. Finally yet importantly, this paper also proposes a probabilistical model to estimate a path duration for each road segment using the highway mobility model. The flexibility of the proposed protocol is evaluated by performing extensive simulations in NS3. We have used SUMO simulator to generate real time vehicular traffic on the roads of Gangnam, South Korea. Comparative analysis of the results confirm that routing overhead for maintaining the network topology is smaller than few previously proposed routing algorithms.

• 정보보호학회논문지
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• 제29권3호
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• pp.685-692
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• 2019

스마트그리드는 기존의 단방향 전력 전송에서 나아가 양방향 정보 교환이 이루어지는 시스템으로 전력의 이동 및 소요량에 대한 실시간 파악이 가능하다. 전력 생산자는 전력 소모량 집계 결과로부터 향후 전력 생산량 예측이 용이하며, 사용자 또한 다수 전력원으로부터의 단위 사용 비용을 고려한 선택적 전력 사용 및 전력 절약 계획 수립이 용이해져 자원의 효율적 생산 및 사용을 가능하게 한다. 반면 자원의 사용 및 이동에 대한 실시간 정보 수집은 개인의 프라이버시를 침해할 수 있는 위험성을 내포하고 있다. 이러한 스마트그리드에서의 전력량 집계 과정에서 프라이버시 침해를 방지하기 위하여, 본 논문에서는 동형 암호화 기법을 활용함으로써 단순 합계를 포함한 복합 연산을 허용하는 유연하면서도 효율적인 전력량 집계 및 분석 기법을 제시한다.

• 4차산업연구
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• 제1권1호
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• pp.23-29
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• 2021

Purpose - Faced with the great change of the 4th industrial revolution and the addition of the COVID-19 pandemic, great confusion and crises are occurring in the retail environment as well. The purpose of this study is to suggest the necessity of establishing a methodology for applying retail tech to offline distribution channels in crisis. Research design, data, and methodology - After examining the recent developments of representative fields to which retail technology is applied, it is rearranged through consideration through previous studies. Result - The retail industry must transform into digital commerce through digital transformation. According to the development of retail technology, the distribution industry is at a time of change from the stage of brokering product and service transactions to a structure that creates value based on information on production and consumption. The business model of the distribution industry must be converted to a platform business model in which both consumers and producers become users. Conclusion - In-depth analysis of the cases has not been conducted, and there are limitations in that the development is somewhat insufficient due to insufficient prior research data. However, it is meaningful to suggest the necessity of finding a methodology for applying retail technology to overcome the crisis of offline retailers through quantitative research on the retail technology area.

• 산업경영시스템학회지
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• 제43권4호
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

• International journal of advanced smart convergence
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• 제9권4호
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• pp.173-178
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• 2020

As the fourth industrial revolution, in which people, objects, and information are connected as one, various fields such as smart energy, smart cities, artificial intelligence, the Internet of Things, unmanned cars, and robot industries are becoming the mainstream, drawing attention to big data. Among them, Smart Grid is a technology that maximizes energy efficiency by converging information and communication technologies into the power grid to establish a smart grid that can know electricity usage, supply volume, and power line conditions. Smart meters are equient that monitors and communicates power usage. We start with the goal of building a virtual smart grid and constructing a virtual environment in which real-time data is generated to accommodate large volumes of data that are small in capacity but regularly generated. A major role is given in creating a software/hardware architecture deployment environment suitable for the system for test operations. It is necessary to identify the advantages and disadvantages of the software according to the characteristics of the collected data and select sub-projects suitable for the purpose. The collected data was collected/loaded/processed/analyzed by the Hadoop ecosystem-based big data platform, and used to predict power demand through deep learning.