• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.212-219
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• 2009

본 논문에서는 웹 관리자가 웹 사이트 분석을 위하여 웹 로그(web log) 분석을 통한 필요한 정보를 추출하고, 추출된 데이터를 분석하여 웹 환경을 개선시키고, 웹 사이트 방문자를 위해 더 좋은 서비스를 할 수 있는 새로운 웹 로그 분석 모델을 제안 한다. 이와 같은 목적을 달성하기 위해 본 논문에서는 웹 로그의 개념 및 유형, 웹 로그의 분석 원칙 및 웹 로그 분석 방법을 고찰하였다. 웹 로그 분석 도구로는 Web Log Expert를 활용하였다. 본 논문에서는 이 도구를 이용하여 웹 방문자 수에 대한 통계분석, 인기가 많은 웹 사이트에 대한 페이지분석 및 방문자 IP 분석 등을 실시하였다.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.123-127
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• 2000

인터넷이 데이터 저장 및 서비스를 위한 도구로 폭넓게 활용되고 있으며, 이 과정에서 웹 서버 방문객에 대한 정보인 로그가 발생된다. 이러한 로그는 방문객 주소, 참조 페이지, 방문 시각 등의 정보를 포함하고 있다. 웹 로그에 대하여 패턴분석(pattern analysis), 군집분석(clustering), 판별분석(classification) 등의 통계적 분석을 통하여 방문객이 관심을 가지는 항목이나 항목간의 연관관계 등 새로운 정보를 생성하여 웹 디자인 또는 비즈니스에의 적용에 대한 연구가 활발히 논의되고 있다. 본 연구에서는 웹 로그 분석에 대하여 소개하고 웹 로그 분석을 위한 방안을 제시하고자 한다.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.317-329
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• 2004

The Web log has caught much attraction for tracing of customer activity. So many researches have been carried on it. As a result, Web log analysis solutions has been developed and launched lately. It has been in the spotlight to the website administrators and people in practical marketing business. In this paper, we made an analysis on the various behavior patterns of customers in cooperation with SAS/AF and SCL modules, based on development of GUI from SAS package for disposal of statistical data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.83-90
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• 2012

With the rapid growth of internet infrastructure, World Wide Web is evolving recently into various services such as cloud computing, social network services. It simply go beyond the sharing of information. It started to provide new services such as E-business, remote control or management, providing virtual services, and recently it is evolving into new services such as cloud computing and social network services. These kinds of communications through World Wide Web have been interested in and have developed user-centric customized services rather than providing provider-centric informations. In these environments, it is very important to check and analyze the user requests to a website. Especially, estimating user preferences is most important. For these reasons, analyzing web logs is being done, however, it has limitations that the most of data to analyze are based on page unit statistics. Therefore, it is not enough to evaluate user preferences only by statistics of specific page. Because recent main contents of web page design are being made of media files such as image files, and of dynamic pages utilizing the techniques of CSS, Div, iFrame etc. In this paper, large log analyzer was designed and executed to analyze web server log to estimate web contents preferences of users. With mapreduce which is based on Hadoop, large logs were analyzed and web contents preferences of media files such as image files, sounds and videos were estimated.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.23-34
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• 2008

The number of web service user is increasing steadily as web-based service is offered in various form. But, web service has a vulnerability such as SQL Injection, Parameter Injection and DoS attack. Therefore, it is required for us to develop Web IDS system and additionally to offer Rule-base intrusion detection/response mechanism against those attacks. However, existing Web IDS system didn't correspond properly on recent web attack mechanism because they didn't including suitable pre-processing procedure on huge web log data. Therfore, we propose an efficient web log pre-processing mechanism for enhancing rule based detection and improving the performance of web IDS base attack response system. Proposed algorithm provides both a field unit parsing and a duplicated string elimination procedure on web log data. And it is also possible for us to construct improved web IDS system.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.157-163
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• 2005

In the Web, the data is generally gathered automatically by Web servers and collected in server or access logs. However, as users access larger and larger amounts of data, query response times to extract information inevitably get slower. A method to resolve this issue is the use of summary tables. In this short note, we design a prototype of summary tables that can efficiently extract information from Web log data. We also present the relative performance of the summary tables against a sampling technique and a method that uses raw data.

• KSCI Review
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• v.14 no.2
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• pp.245-254
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• 2006

Web Forensics algorithm used to an extraction of technical Web Forensics data to be adopted to proof data regarding a crime cyber a computer at data of a great number of log History is an essential element. Propose Web Forensics algorithm, and design at these papers, and try to implement in a Web server system of an actual company. And make the Web dispatch Loging system configuration experiment that applied integrity regarding Web log History information or authentication regarding an information source. Design Web Forensics algorithm and the Flow which used for Web log History analyses at server of e-mail, webmail, HTTP (Web BBS, Blog etc.), FTP, Telnet and messengers (MSN, NateOn, Yahoo, DaumTouch. BuddyBuddy, MsLee, AOL, SoftMe) of a company, and implement through coding. Therefore have a purpose of these paper to will contribute in scientific technical development regarding a crime cyber a computer through Web Forensics.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.117-126
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• 2007

Web Forensics algorithm used to an extraction of technical Web Forensics data to be adopted to proof data regarding a crime cyber a computer at data of a great number of log History is an essential element. Propose Web Forensics algorithm, and design at these papers, and try to implement in a Web server system of an actual company. And make the Web dispatch Loging system configuration experiment that applied integrity regarding Web log History information or authentication regarding an information source. Design Web Forensics algorithm and the Flow which used for Web log History analyses at server of e-mail, webmail, HTTP (Web BBs. Blog etc.), FTP, Telnet and messengers (MSN, NateOn, Yahoo, DaumTouch, BuddyBuddy, MsLee, AOL, SoftMe) of a company, and implement through coding. Therefore have a purpose of these Paper to will contribute in scientific technical development regarding a crime cyber a computer through Web Forensics.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.231-241
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• 2019

Web Usage Mining (WUM) is one part of Web mining and also the application of data mining technique. Web mining technology is used to identify and analyze user's access patterns by using web server log data generated by web users when users access web site. So first of all, it is important that the data should be acquired in a reasonable way before applying data mining techniques to discover user access patterns from web log. The main task of data acquisition is to efficiently obtain users' detailed click behavior in the process of users' visiting Web site. This paper mainly focuses on data acquisition stage before the first stage of web usage mining data process with activities like data acquisition strategy and field extraction algorithm. Field extraction algorithm performs the process of separating fields from the single line of the log files, and they are also well used in practical application for a large amount of user data.