• Title/Summary/Keyword: 인터넷 환경

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A Study on the Difference between Young and Old Generation of SNS Behavior (SNS(social network service)활용에 대한 세대별 차이 연구)

  • Hwang, Yoon Yong;Lee, Ki Sang;Choi, Soow-A
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.1
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    • pp.63-77
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    • 2015
  • As social network service(SNS) environments have been changed and increased, people perceive SNSs as a part of their daily lives. Therefore mutual communication activities based on the Internet and its influences are expanding continuously. This paper explored the difference between consumers' emotional well-being level and social capital formed through SNSs. Given that the reason of using SNS and its utilization can be different depending on consumers, this paper also examines generation differences. Hence, we examine how the forms of emotional well-being and social capital in SNSs can be different according to each generation. We conducted a survey targeting the consumers who have an experience of using online SNS and looked into the effects of emotional well-being and social capital among generations using eighty three valid samples. In this study, we find that there are differences on the effects of the sizes and the types of social capital formed through SNS, depending on the generations. In particular, the size of social capital from younger generation was larger compared to the older generation and bridging social capital, one of social capital types, was also bigger in the younger generation compared to the older generation. Although general emotional well-being was not differentiated among the generations, we could find a generation difference by showing that older generation's negative well-being, one of emotional well-being types, was more sensitive than younger generation. Based on such results, this paper proposes SNS utilization plan sub-divided by generations, suggesting management direction of online social networks.

Implementation of a Windows NT Based Stream Server for Multimedia School Systems (멀티미디어 교실을 위한 윈도우 NT 기반 스트림 서버 구현)

  • 손주영
    • Journal of Korea Multimedia Society
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    • v.2 no.3
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    • pp.277-288
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    • 1999
  • A distributed multimedia school system is developed for the multimedia classroom at high school and university. The system is designed and implemented for students to improve the learning efficiency through the personalized multimedia contents and pace of learning. The previously developed multimedia information retrieval systems have some limitations on being applied to the multimedia classroom: expensive cost per stream or poor retrieval quality inappropriate for education, unscalability of system and service, unfamiliar proprietary client environment, and difficulty for teachers to use the authoring tools and manage the authored teaching materials. The system we developed overcomes the above problems. It is so scalable as to be applicable not only to a segmented classroom but also to the world wide Internet. The stream server is one of the components of the system: stream servers clients, a service gateway system, and a authoring management system. This paper describes the design and implementation of the stream server. A single stream server can simultaneously playback the multimedia streams as many as clients at one classroom. This is achieved only by the software engine without any changes of the hardware architecture. The systematic coupling with other components gives the scalability of the system and the flexibility of services.

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A Technique Getting Fast Masks Using Rough Division in Dynamic ROI Coding of JPEG2000 (JPEG2000의 동적 ROI 코딩에서 개략적인 분할을 이용한 빠른 마스크 생성 기법)

  • Park, Jae-Heung;Lee, Jum-Sook;Seo, Yeong-Geon;Hong, Do-Soon;Kim, Hyun-Joo
    • The KIPS Transactions:PartB
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    • v.17B no.6
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    • pp.421-428
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    • 2010
  • It takes a long time for the users to view a whole image from the image server under the low-bandwidth internet environments or in case of a big sized image. In this case, as there needs a technique that preferentially transfers a part of image, JPEG2000 offers a ROI(Region-of-Interest) coding. In ROI coding, the users see the thumbnail of image from the server and specifies some regions that they want to see first. And then if an information about the regions are informed to the server, the server preferentially transfers the regions of the image. The existing methods requested a huge time to compute the mask information, but this thesis approximately computes the regions and reduces the creating time of the ROI masks. If each code block is a mixed block which ROI and background are mixed, the proper boundary points should be acquired. Searching the edges of the block, getting the two points on the edge, to get the boundary point inside the code block, the method searches a mid point between the two edge points. The proposed method doesn't have a big difference compared to the existing methods in quality, but the processing time is more speedy than the ones.

A Study on Effective Instructional Design using e-NIE(electronic-Newspaper In Education) (효과적인 e-NIE 수업설계 방안에 관한 연구)

  • Park, JI-Yeon;Chun, Seok-Ju
    • 한국정보교육학회:학술대회논문집
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    • 2010.08a
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    • pp.127-134
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    • 2010
  • In the information oriented society, a good lesson helps learners to develop self-learning ability. To give a good lesson, teachers should teach with details in learning contents that learners can understand easily, not with abstract and generalized concepts in the textbook. And they also should find the effective instructional media to give students the learning contents. Since the newspaper carries the most current and up-to-date source of information about various fields, if it is used as the teaching material in the classroom, it can help students to learn useful and practical knowledge. Therefore, newspapers are so-called 'living textbook'. NIE which enables students to enhance their ability to utilize the information and to learn wisdom about life, is already actively applied to the educational activities. And e-learning system and the electronic newspaper that make learning happen to anyone anytime anywhere, appears with the advancements in information technology and changing educational paradigm. This changed circumstance make the field and the way of NIE enlarge to e-NIE. e-NIE is the educational media that helps the learners to learn the way of learning. But the study about e-NIE through designing a teaching plan systematically has not been made completely. Therefore, this research aims to find out the characteristics of e-NIE and the effective way of designing a teaching plan that fits the characteristics of e-NIE.

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A Study of Statistical Learning as a CRM s Classifier Functions (CRM의 기능 분류를 위한 통계적 학습에 관한 연구)

  • Jang, Geun;Lee, Jung-Bae;Lee, Byung-Soo
    • The KIPS Transactions:PartB
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    • v.11B no.1
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    • pp.71-76
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    • 2004
  • The recent ERP and CRM is mostly focused on the conventional function performances. However, the recent business environment has brought the change in market due to the rapid progress of internet and e-commerce. It is mostly becoming e-business and spreading out as development of the relationship with other cooperating companies, the rapid progress of the relationship with customers, and intensification competitive power through the development of business progress in the organization. CRM(custom relationship management) is a kind of the marketing progress which forms, manages, and intensifies the relationship between the customers and companies to manage the acquired customers and increase the worth of customers for the company. It needs the system base which analyzes the information of customers since it functions on the basis of various information about customers and is linked to the business category such as producing, marketing, and decision making. Since ERP is extending its function to SCM, CRM, and SEM(strategic Enterprise Management), the 21 century s ERP develop as the strategy tool of e-business and, as the mediation for this, will subdivide the functions of CRM effectively by the analogic study of data. Also, to accomplish classification work of the file which in existing becomes accomplished with possibility work with an automatic movement with the user will be able to accomplish a more efficiently work the agent which in order leads the machine studying law, it is one thing with system feature.

Forecasting Future Market Share between Online-and Offline-Shopping Behavior of Korean Consumers with the Application of Double-Cohort and Multinomial Logit Models (생잔효과와 다중로짓모형으로 분석한 구매형태별 시장점유율 예측)

  • Lee, Seong-Woo;Yun, Seong-Do
    • Journal of Distribution Research
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    • v.14 no.1
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    • pp.45-65
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    • 2009
  • As a number of people using the internet for their shopping steadily rises, it is increasingly important for retailers to understand why consumers decide to buy products via online or offline. The main purpose of this study is to develop and test a model that enhance our understanding of how consumers respond future online and offline channels for their purchasing. Rather than merely adopting statistical models like most other studies in this field, the present study develops a model that combines double-cohort method with multinomial logit model. It is desirable if one can adopt an overall encompassing criterion in the study of consumer behaviors form diverse sales channels. This study uses the concept of cohort or aging to enable this comparison. It enables us to analyze how consumers respond to online and offline channels as people aged by measuring their shopping behavior for an online and offline retailers and their subsequent purchase intentions. Based on some empirical findings, this study concludes with policy implications and some necessary fields of future studies desirable.

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A Study on Improvement of Inspection Items for Activation of the Information Security Pre-inspection (정보보호 사전점검 활성화를 위한 점검항목 개선 연구)

  • Choi, Ju Young;Kim, JinHyung;Park, Jung-Sub;Park, Choon Sik
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.4
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    • pp.933-940
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    • 2015
  • IT environments such as IoT, SNS, BigData, Cloud computing are changing rapidly. These technologies add new technologies to some of existing technologies and increase the complexity of Information System. Accordingly, they require enhancing the security function for new IT services. Information Security Pre-inspection aims to assure stability and reliability for user and supplier of new IT services by proposing development stage which considers security from design phase. Existing 'Information Security Pre-inspection' (22 domains, 74 control items, 129 detail items) consist of 6 stage (Requirements Definition, Design, Training, Implementation, Test, Sustain). Pilot tests were executed for one of IT development companies to verify its effectiveness. Consequently, for some inspection items, some improvement requirements and reconstitution needs appeared. This paper conducts a study on activation of 'Information Security Pre-inspection' which aims to construct prevention system for new information system. As a result, an improved 'Information Security Pre-inspection' is suggested. This has 16 domains, 54 inspection items, 76 detail items which include some improvement requirements and reconstitution needs.

A Practical Feature Extraction for Improving Accuracy and Speed of IDS Alerts Classification Models Based on Machine Learning (기계학습 기반 IDS 보안이벤트 분류 모델의 정확도 및 신속도 향상을 위한 실용적 feature 추출 연구)

  • Shin, Iksoo;Song, Jungsuk;Choi, Jangwon;Kwon, Taewoong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.2
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    • pp.385-395
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    • 2018
  • With the development of Internet, cyber attack has become a major threat. To detect cyber attacks, intrusion detection system(IDS) has been widely deployed. But IDS has a critical weakness which is that it generates a large number of false alarms. One of the promising techniques that reduce the false alarms in real time is machine learning. However, there are problems that must be solved to use machine learning. So, many machine learning approaches have been applied to this field. But so far, researchers have not focused on features. Despite the features of IDS alerts are important for performance of model, the approach to feature is ignored. In this paper, we propose new feature set which can improve the performance of model and can be extracted from a single alarm. New features are motivated from security analyst's know-how. We trained and tested the proposed model applied new feature set with real IDS alerts. Experimental results indicate the proposed model can achieve better accuracy and false positive rate than SVM model with ordinary features.

A Study on Automatic Classification Technique of Malware Packing Type (악성코드 패킹유형 자동분류 기술 연구)

  • Kim, Su-jeong;Ha, Ji-hee;Lee, Tae-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.5
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    • pp.1119-1127
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    • 2018
  • Most of the cyber attacks are caused by malicious codes. The damage caused by cyber attacks are gradually expanded to IoT and CPS, which is not limited to cyberspace but a serious threat to real life. Accordingly, various malicious code analysis techniques have been appeared. Dynamic analysis have been widely used to easily identify the resulting malicious behavior, but are struggling with an increase in Anti-VM malware that is not working in VM environment detection. On the other hand, static analysis has difficulties in analysis due to various packing techniques. In this paper, we proposed malware classification techniques regardless of known packers or unknown packers through the proposed model. To do this, we designed a model of supervised learning and unsupervised learning for the features that can be used in the PE structure, and conducted the results verification through 98,000 samples. It is expected that accurate analysis will be possible through customized analysis technology for each class.

Network Anomaly Detection Technologies Using Unsupervised Learning AutoEncoders (비지도학습 오토 엔코더를 활용한 네트워크 이상 검출 기술)

  • Kang, Koohong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.30 no.4
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    • pp.617-629
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    • 2020
  • In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.