• 경영과학
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• 제13권1호
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• pp.29-46
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• 1996

In the past decade, considerable effort has been devoted unsuccessfully to the development of information technology (IT) evaluation frameworks in the information systems area. Based on the literature review in this area and the decision analysis field, two competing evaluation frameworks are developed in this study: the direct evaluation framework and the indirect evaluation framework. A case study on Firm K shows that the latter is more practically efficient and theoretically appropriate but requires the adequate training for practitioners in order not to get confused the weight of an evaluation variable with the product of this weight and the score of the variable. Another finding is that Weill's conversion effectiveness is neither possible nor necessary to measure in the process of evaluating an IT although it is in theory an important concept.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1079-1084
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• 2006

Since the focus of QFD is placed on the early stage of product development, the uncertainty in the input information of QFD is inevitable. If the uncertainty is neglected, the QFD analysis results can be misleading. This paper proposes an extended version of the QFD methodology, called Robust QFD, which is capable of considering the uncertainty of the input information and the resulting variability of the output. The proposed framework aims to model, analyze, and dampen the effects of the uncertainty and variability in a systematic manner. The proposed framework is demonstrated through a case study on the ADSL-based high-speed internet service.

• Agribusiness and Information Management
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• 제1권2호
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• pp.23-42
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• 2009

As technology develops, more advanced technologies involving GPS, GIS, RFID and sensor networks have been adopted in agriculture sector for u-Farm. However, technology adoptions have been evaluated as ineffective. Farmers and agri-business have low level of understanding on technology so it is not efficiently utilized. This study introduces a case of RFID/sensor networks of mushroom farm as a u-Farm case study, focusing on developing a framework for analysis of u-Farm investment returns. RFID and sensor networks improve real-time production control, processing management, and traceability. Integration of RFID and sensor networks leads to innovation into the mushroom farm, reducing labor cost, increasing productivity, and improving quality of the mushroom. The ROI which is used as an indicator of performance indicator is 413%.

• 정보통신설비학회논문지
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• 제9권1호
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• pp.24-28
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• 2010

The Quality of Experience (QoE) of next Generation wired/wireless network services based upon IP networking is becoming a popular issue in recent years. The user experience of Internet services such as IPTV, online game, web surfing and etc, are becoming the most desirable factors to service providers to improve service performance and customer's satisfaction. However, collecting user experience from customers and obtaining the QoE parameters from the Quality of Service (QoS) parameters such as bandwidth, delay, jitter or admission control algorithm, are difficult subjects because of the various service types and user characteristics. In this paper, we propose a framework which contains service classification, QoE analysis and service enhancement steps for a suitable QoE measurement and management protocol. We define the user satisfaction indicators of the Internet services, classify the categories of each type of services, and analyse the Key Performance Indicator (KPI) in each type of services to perform the QoS parameters and improving the service qualities.

• Asia pacific journal of information systems
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• 제30권2호
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• pp.420-438
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• 2020

Recently, with the advance of the wireless Internet access via mobile devices, a myriad of game development companies have forayed into the mobile game market, leading to intense competition. To survive in this fierce competition, mobile game developers often try to get a grasp of the rapidly changing needs of their customers by operating their own official communities where game users freely leave their requests, suggestions, and ideas relevant to focal games. Based on the heuristic-systematic model (HSM) and the data quality (DQ) framework, this study derives key content, non-content, and hybrid cues that can be utilized when game developers accept suggested postings in these online communities. The results of hierarchical multiple regression analysis show that relevancy, timeliness, amount of writing, and the number of comments are positively associated with mobile game developers' knowledge adoption. In addition, title attractiveness mitigates the relationship between amount of writing/the number of comments and knowledge adoption.

• 컴퓨터교육학회논문지
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• 제17권6호
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• pp.71-80
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• 2014

최근 사이버테러 및 개인정보유출 등의 정보보안관련 이슈가 대두됨에 따라 정보보호 인력 양성을 위해 많은 정보보호관련 학과가 신설되고 있다. 하지만 컴퓨터공학 등의 기존 IT 학과와의 차별성이 부족하고 실제 현장에서 원하는 인재를 양성하지 못하고 있는 실정이다. 이러한 문제를 개선하기 위해 정보보호 직무체계와 각 직무에 필요한 역량 및 기술들을 제시한 기존의 연구를 조사했다. 그리고 미국의 NICE에서 제시된 역량을 중심으로 국내 대학 정보보호관련 학과의 교육과정을 분석했다. 그 결과 정보보호 제품을 개발하는 분야를 위주로 교육과정이 편성되어 있는 것을 확인했고 교육과정이 정보보호 직무체계별 역량을 중심으로 개선할 필요가 있었다. 이 결과를 통해 이후 정보보호 학과의 교육과정 개선을 위한 기초 연구로 활용되고자 한다.

• 정보보호학회논문지
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• 제18권1호
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• pp.139-148
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• 2008

정보기술의 발전은 비즈니스 환경의 변화는 물론 대형 산업 시설의 자동화에 많은 변화를 가져왔다. 전력, 수자원, 에너지, 교통, 통신, 등은 국가의 안보와 국민 생활의 안정 그리고 국가 경제발전의 기반을 형성하는 국가의 주요 기반시설이며 이들 모두 산업제어 시스템에 의해 통제되고 있다. 또 비즈니스 환경의 변화는 조직의 모든 시스템을 통합하고 있어 경영정보시스템과 산업제어 시스템의 통합이 이루어지고 있다. 이에 따라 산업제어 시스템의 표준화와 개방형 시스템으로 전환이 이루어지고 있어 더욱 보안의 중요성이 커지고 있다. 제어시스템 보안에 대한 연구가 기술, 관리, 환경 등 다양한 분야에서 추진되고 있다. 그럼에도 제어시스템 감사에 대한 연구는 아직 미약하다. 정부는 최근 정부 및 주요 공공 시스템에 대한 정보시스템 감리를 의무화하여 안정성, 효율성, 효과성을 평가하고 있다. 또 주요정보통신기반시설에 대해서는 취약점 분석을 하고 그 개선 작업을 하도록 의무화하고 있다. 그럼에도 제어시스템에 대한 감리를 하지 않고 있고 제어시스템에 대한 보안 아키텍처나 감리 프레임워크도 준비되어 있지 않다. 본 연구는 제어시스템 감리를 위한 정보보안 아키텍처와 정보보안 감리 프레임워크를 제시하여 감리의 기반을 마련하였다.

• 한국공간정보시스템학회 논문지
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• 제10권1호
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• pp.41-49
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• 2008

본 논문은 제주 택시 텔레매틱스 사업에서 수집된 차량의 히스토리 데이터를 온라인 혹은 오프라인으로 효율적으로 분석하기 위한 스테이트 다이어그램을 정의하고 이에 기반하여 택시의 운행과 배차에 대한 분석 결과를 산출하는 것을 목표로 한다. 차량에서 수집된 정보는 기본적인 GPS정보 이외에 차량의 상태를 나타내는 필드를 포함하고 있으며 지도 정보의 결합으로 맵 매칭 및 도로상에서의 위치비율 등을 계산할 수 있다. 구축된 레코드들에 의해 택시의 승객 탑승 빈도, 탑승시 이동 거리, 탑승시간 등을 분석할 수 있으며 콜 택시의 중요한 성능 척도가 되는 배차 후 차량의 이동 거리 및 이동 시간을 분석하여 배차 방식의 효율성을 검증할 수 있다. 이 정보는 심도 있는 분석을 수반하여 향후 교통정보 예측, 혼잡상황 회피 등의 다양한 응용의 진화를 가능하게 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권2호
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• pp.766-783
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• 2012

Recently, many malicious users have attacked web browsers using JavaScript code that can execute dynamic actions within the browsers. By forcing the browser to execute malicious JavaScript code, the attackers can steal personal information stored in the system, allow malware program downloads in the client's system, and so on. In order to reduce damage, malicious web pages must be located prior to general users accessing the infected pages. In this paper, a novel framework (JsSandbox) that can monitor and analyze the behavior of malicious JavaScript code using internal function hooking (IFH) is proposed. IFH is defined as the hooking of all functions in the modules using the debug information and extracting the parameter values. The use of IFH enables the monitoring of functions that API hooking cannot. JsSandbox was implemented based on a debugger engine, and some features were applied to detect and analyze malicious JavaScript code: detection of obfuscation, deobfuscation of the obfuscated string, detection of URLs related to redirection, and detection of exploit codes. Then, the proposed framework was analyzed for specific features, and the results demonstrate that JsSandbox can be applied to the analysis of the behavior of malicious web pages.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.4021-4037
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• 2018

In network intrusion detection research, two characteristics are generally considered vital to building efficient intrusion detection systems (IDSs): an optimal feature selection technique and robust classification schemes. However, the emergence of sophisticated network attacks and the advent of big data concepts in intrusion detection domains require two more significant aspects to be addressed: employing an appropriate big data computing framework and utilizing a contemporary dataset to deal with ongoing advancements. As such, we present a comprehensive approach to building an efficient IDS with the aim of strengthening academic anomaly detection research in real-world operational environments. The proposed system has the following four characteristics: (i) it performs optimal feature selection using information gain and branch-and-bound algorithms; (ii) it employs machine learning techniques for classification, namely, Logistic Regression, Naïve Bayes, and Random Forest; (iii) it introduces bulk synchronous parallel processing to handle the computational requirements of large-scale networks; and (iv) it utilizes a real-time contemporary dataset generated by the Information Security Centre of Excellence at the University of Brunswick (ISCX-UNB) to validate its efficacy. Experimental analysis shows the effectiveness of the proposed framework, which is able to achieve high accuracy, low computational cost, and reduced false alarms.