• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1797-1804
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• 2015

Integrated log management system can help to predict the risk of security and contributes to improve the security level of the organization, and leads to prepare an appropriate security policy. In this paper, we have designed and implemented a Hadoop-based log analysis system by using distributed database model which can store large amount of data and reduce analysis time by automating log collecting procedure. In the proposed system, we use the HBase in order to store a large amount of data efficiently in the scale-out fashion and propose an easy data storing scheme for analysing data using a Hadoop-based normal expression, which results in improving data processing speed compared to the existing system.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.1-10
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• 2021

Log data accumulated in the Learning Management System (LMS) provide high-quality information for the learning process of students. Until now, various studies have been conducted to predict students' academic achievement using LMS log data. However, previous studies were based on relatively small sample sizes of students and courses, limiting the possibility of generalization. This study developed and validated a deep neural network model for the early prediction of academic achievement of college students using massive LMS log data. To this end, we used 78,466,385 cases of LMS log data and 165,846 cases of grade data. The proposed model predicted the excellent-grade students with a high level of accuracy from the beginning of the semester. Meanwhile, the prediction accuracy for the moderate and underachieving groups was relatively low, but the accuracy improved as the time points of the prediction were delayed. This study is meaningful in that we developed an early prediction model based on a deep neural network with sufficient accuracy for practical utilization by only using LMS log data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.101-114
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• 2011

As it seems like critical information leakages have been increasing due to industrial espionage and malicious internal users, the importance of introducing audit and log security technology is growing every now and then. In this paper, we suggest the session logging system for the company's internal control to meet the SOX legislation level, by monitoring and analyzing users behaviors connecting to the business-critical Operating System. The system proposed in this paper aims to monitor the user's illegal activities in the Operating System, and to present the clear evidence of purpose of those activities by detailed logs. For this purpose, we modified Operating System by adding multiple services suggested in this paper. These services utilize interfaces provided by the existing Operating System and add functions to control access and get logs. The system saves and manages session logs of users or administrators connected to the server with centralized log storage. And the system supports session log searching and lookup features required by SOX legislation for the company's internal controls with the level of computer forensics and logging technology.

• Convergence Security Journal
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• v.15 no.2
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• pp.33-41
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• 2015

A safe Linux system for security enhancement should have an audit ability that prohibits an illegal access and alternation of data as well as trace ability of illegal activities. In addition, construction of the log management and monitoring system is a necessity to clearly categorize the responsibility of the system manager or administrator and the users' activities. In this paper, the Linux system's Security Log is analyzed to utilize it on prohibition and detection of an illegal protrusion converting the analyzed security log into a database. The proposed analysis allows a safe management of the security log. This system will contribute to the enhancement of the system reliability by allowing quick response to the system malfunctions.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.1-17
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• 2009

E-Catalogs which describe products or services are one of the most important data for the electronic commerce. E-Catalogs are created, updated, and removed in order to keep up-to-date information in e-Catalog database. However, when the number of catalogs increases, information integrity is violated by the several reasons like catalog duplication and abnormal classification. Catalog search, duplication checking, and automatic classification are important functions to utilize e-Catalogs and keep the integrity of e-Catalog database. To implement these functions, probabilistic models that use statistics of index words extracted from e-Catalogs had been suggested and the feasibility of the methods had been shown in several papers. However, even though these functions are used together in the e-Catalog management system, there has not been enough consideration about how to share common data used for each function and how to effectively manage statistics of index words. In this paper, we suggest a method to implement these three functions by using simple SQL supported by relational database management system. In addition, we use materialized views to reduce the load for implementing an application that manages statistics of index words. This brings the efficiency of managing statistics of index words by putting database management systems optimize statistics updating. We showed that our method is feasible to implement three functions and effective to manage statistics of index words with empirical evaluation.

• Water for future
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• v.55 no.5
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• pp.46-49
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• 2022

• Review of KIISC
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• v.23 no.6
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• pp.90-99
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• 2013

최근 급증하고 있는 고도화된 사이버 공격은 많은 피해를 낳고 있다. 이러한 문제를 미연에 방지하기 위해 각종 보안 솔루션의 도입으로 보안 시스템 환경이 복잡하게 변하게 되었다. 보안 관리자는 복잡한 환경으로 인해 보안 시스템 관리의 어려움으로 우수한 보안 솔루션이 있음에도 위협에 제대로 대처하지 못하고 있다. 본 논문에서는 보안시스템을 체계적으로 관리할 수 있고, IT 시스템에서 생성되는 이벤트와 로그를 통합해 늘어나고 있는 보안 위협에 적절한 대응이 가능하도록 도와주는 보안 시스템 관리 솔루션인 SIEM(Security Information and Event Management)에 대해 알아보고자 한다. 고도화되고 있는 사이버 공격과 복잡해진 클라우드 컴퓨팅, 데이터가 대량화됨에 따라 생겨난 빅데이터, 갈수록 강화되고 있는 컴플라이언스 요구사항을 만족할 수 있는 방안을 모색해봄으로써 SIEM이 앞으로 나아가야 할 방향에 대해 알아보고자 한다.

• Spatial Information Research
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• v.10 no.1
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• pp.165-183
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• 2002

The master plan for the land management information system development was established in 1997 and demonstration projects were carried out in Nam-gu, Daegu Metropolis in 1998. As of the end of 2001, 12 project areas have completed installing the land management information system and are now utilizing it in operations or in trial operation and 88 areas are still under construction. Sixteen metropolises and provinces and 232 cities, counties and districts plan to complete the development of land management information system by 2004 and additionally Install a land information center to manage and maintain the land management information system. The land management information system was introduced as one of information technologies to solve the problems arising in the operations of land management and administration. It inevitably accompanies a radical change of working environment, from analogue to digital. It is obviously not a simple job and largely depends on how to entice the officials working in analogue settings into a digitalized world. Therefore, it is not too much to say that the success of the land management information system development project depends on how to rationally adapt the analogue land administrations to a digital environment.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.735-744
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• 2021

Maintaining the lifetime of a product is one of the objectives of quality control. In real processes, most samples are constructed with censored data because, in many situations, we cannot measure the lifetime of all samples due to time or cost problems. In this paper, we propose two cumulative sum (CUSUM) control charting procedures to monitor the mean of type I right-censored lognormal lifetime data. One of them is based on the likelihood ratio, and the other is based on the binomial distribution. Through simulations, we evaluate the performance of the two proposed procedures by comparing the average run length (ARL). The overall performance of the likelihood ratio CUSUM chart is better, especially this chart performs better when the censoring rate is low and the shape parameter value is small. Conversely, the binomial CUSUM chart is shown to perform better when the censoring rate is high, the shape parameter value is large, and the change in the mean is small.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.1-6
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• 2022

Lifelog is a digital record of an individual collected from various digital sensors, and includes activity amount, sleep information, weight change, body mass, muscle mass, fat mass, etc. Recently, as wearable devices have become common, a lot of high-quality lifelog data is being produced. Lifelog data shows the state of an individual's body, and can be used not only for individual health care, but also for causes and treatment of diseases. However, at present, AI/ML-based correlation analysis and personalization are not reflected. It is only at the level of presenting simple records or fragmentary statistics. Therefore, in this paper, the correlation/relationship between lifelog data and disease, and AI/ML technology inside lifelog data are examined, and furthermore, a lifelog data analysis process based on AI/ML is proposed. The analysis process is demonstrated with the data collected in the actual Galaxy Watch. Finally, we propose a future convergence service roadmap including lifelog data, diet, health information, and disease information.