• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.1109-1133
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• 2013

In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

• The KIPS Transactions:PartC
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• v.8C no.5
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• pp.657-666
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• 2001

In this paper, it is proposed the management items for voice traffic using CDRs so that global carriers can treat and manage the voice traffic for a customer, and defined computational expressions to produce the management items. From them, we have designed the management system, which is composed of web interface module, analysis module, data collection module and database management module, and have improved the availability and convenience of the system using web technologies. In addition, we have tested these items using CDRs in real environments that are collected by the global carrier in order to verify their validity. It is expected that the proposed web based voice traffic management system provide a global carrier with network information collection, fault detection/trouble-shooting and high quality of service through analyzing the characteristics of subscribers.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.5
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• pp.37-45
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• 2004

As Internet technologies are mature, many new applications that are different characteristics are emerging. Recently we see wide use of P2P(Peer to Peer) applications of which traffic shows different statistical characteristics compared with traditional application such as web(HTTP) and FTP(File Transfer Protocol). In this paper, we measured subscriber network of KT(Korea Telecom) to analyze P2P traffic characteristics. We show flow characteristics of measured traffic. We also estimate Hurst parameter of P2P traffic and compare self-similarity with web traffic. Analysis results indicate that P2P traffic is much bustier than web traffic and makes both upstream traffic and downstream traffic be symmetric. To predict parameters related QoS such as packet loss and delays we model P2P traffic using two self-similar traffic models and predict both loss probability and mm delay then compare their accuracies. With simulation we show that the self-similar traffic models we derive predict the performance of P2P traffic accurately and thus when we design a network or evaluate its performance, we can use the P2P traffic model as reference input traffic.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.94-99
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• 2016

Application layer attacks have for years posed an ever-serious threat to network security, since they always come after a technically legitimate connection has been established. In recent years, cyber criminals have turned to fully exploiting the web as a medium of communication to launch a variety of forbidden or illicit activities by spreading malicious automated software (auto-ware) such as adware, spyware, or bots. When this malicious auto-ware infects a network, it will act like a robot, mimic normal behavior of web access, and bypass the network firewall or intrusion detection system. Besides that, in a private and large network, with huge Hypertext Transfer Protocol (HTTP) traffic generated each day, communication behavior identification and classification of auto-ware is a challenge. In this paper, based on a previous study, analysis of auto-ware communication behavior, and with the addition of new features, a method for classification of HTTP auto-ware communication is proposed. For that, a Not Only Structured Query Language (NoSQL) database is applied to handle large volumes of unstructured HTTP requests captured every day. The method is tested with real HTTP traffic data collected through a proxy server of a private network, providing good results in the classification and detection of suspicious auto-ware web access.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Korean journal of communication and information
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• v.64
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• pp.109-135
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• 2013

This study is for empirical verification of the influence of the introduction of smart phone on using the portal sites that were affected the most in the previous media environment. To achieve this, Web traffic data that are the result of smart phone users' practical Web uses have collected longitudinally and analyzed. The research results are the following: First, the use hours of portal sites have decreased about 15% and the page views have did about 35%, since using smart phones was diffused and habituated in earnest during the past two years. Using the community, news media, video, mobile, and game section of portal site sections have reduced. Second, the portal site portion of using smart phone Web is much more than that portion of using PC Web. More than two thirds of smart phone Web use traffic occurs in using portal sites, while more than one third of PC Web use traffic does in using that. Using the news media section is the most of using portal site sections on a smart phone. Third, since the introduction of smart phone, using the news media, communication, and life section of portal site sections have greatly increased, while the community, mobile, and game section have greatly decreased in the aggregate.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.79-85
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• 2005

In order to handle client's requests while multiple servers seamlessly work in the web server cluster environment, it is vital to implement a router that execute a routing using TCP information and requested target content. The implemented package software measured packet volume that was generated from data generator, virtual server, and server 1, 2, 3, and could find out traffic distribution toward Server 1, 2, 3. As the result of the study shows, Round Robin Algorithm ensured definite traffic distribution, unless incoming data loads differ much. Although error levels were high in some partial cases, they were eventually alleviated by repeated tests for a longer time.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.565-567
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• 2002

DDOS공격은 최근 인터넷 환경에서 큰 위험요소로 부각되고 있다. 하지만, DDOS공격을 완벽하게 막아내는 것은 현재까지 알려진 방법으로는 거의 불가능하다. 그 이유는DDOS 공격이 Vulnerability Exploit을 이용한 공격방법이 아니라 Network Resource를 고갈시켜서 공격대상 호스트의 서비스를 차단하기 때문이다. 그래서, DDOS공격을 방어하기 위해서는 DDOS공격 트래픽에 대한 정확한 분석과 탐지가 선행되어야 한다. 본 논문을 통해서 여러 가지 DDOS공격 Traffic의 특징을 살펴보고, Web traffic과의 차이를 통해 DDOS traffic을 탐지하는 방법을 제안하고자 한다.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.652-653
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• 2015

This study investigates the effect of real-time traffic information on the traffic flows in Korea. Recently, the development of smartphones has made it easier to use the route guidance service based on real-time traffic information. By the Big Data analysis in the study, it was found that the number of postings on the web community sites increased sharply in 2010 and 2011 when the smartphones spread widely. In the analysis of the traffic speeds by time, the average traffic speeds for morning and evening rush hours on weekdays from 2009 to 2014 of the 142 sections in the 6 national highways in Gyeonggi-do, Korea were used. From the results of the analysis, it was found that the percentage of the number of sections with the improved traffic flows increased greatly in 2012 compared to 2011. The findings of the study indicate the effect of the real-time traffic information on improving traffic flows.

• Journal of Korean Medicine Rehabilitation
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• v.27 no.4
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• pp.131-145
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• 2017

Objectives The purpose of this study is to understand current status of Korean Medicine treatment practice patterns for traffic injuries by web-based survey. Methods The structured questionnaire was distributed by a web based survey to 1,630 potential respondents by email from December 19th in 2016 to February 13th in 2017. All data were statistically analysed. Results The response rate was 79.4%. According to the analysis of the outcome of the survey, 88.0% of the participants felt necessity of the development of Korean medicine clinical practice guidelines (CPGs) for traffic injuries. Survey results showed cognitive degree about Korean Medicine CPGs' necessity, individual Korean medicine treatments and requirement for extending insurance coverage for patients with traffic injuries. Conclusions This survey study helps to determine current clinical practice patterns of Korea medicine treatments for traffic injuries. These results further anticipate to provide basic data for CPGs for traffic injuries.