• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.123-132
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• 2021

Malicious activities of Botnets are responsible for huge financial losses to Internet Service Providers, companies, governments and even home users. In this paper, we try to confirm the possibility of detecting botnet traffic by applying the deep learning model Convolutional Neural Network (CNN) using the CTU-13 botnet traffic dataset. In particular, we classify three classes, such as the C&C traffic between bots and C&C servers to detect C&C servers, traffic generated by bots other than C&C communication to detect bots, and normal traffic. Performance metrics were presented by accuracy, precision, recall, and F1 score on classifying both known and unknown botnet traffic. Moreover, we propose a stackable botnet detection system that can load modules for each botnet type considering scalability and operability on the real field.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.33-38
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• 2021

The convergence trend is the core of the 4th industrial revolution, and due to such expectations and possibilities, various countermeasures are being sought in diverse fields. This study conducted a quantitative analysis to identify the trend of convergence research over the past 10 years. Specifically, major research keywords were extracted, word cloud techniques were applied, and visualized to identify trends in academic research on convergence. To this end, research papers from 2012 to 2020 published in journal of digital convergence were investigated. The analysis period was divided into two periods: the former 4 years(2012-2015) and the latter 4 years(2016-2019) to confirm the difference in research trends. In addition, the research papers of 2020 were analyzed in order to more clearly understand the changes in the research trend of the last year due to the COVID-19. The results of this study are significant in that they can be used as useful basic data for future research and to understand research trends as keywords in the field of convergence.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.994-1003
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• 2020

In this paper, we investigated the current issues on the KPAS(Korean Public Alert Service) by News analysis. News articles, from May 15, 2005 to April 30, 2020, were collected with the key word of 'KPAS' through the News Big-Data System provided by the Korea Press Foundation. The results of the content analysis are as follows. First, the issues on alert presentation were categorized by alarm sound, message content, alert level, transmission frequency, delay, reception range, time of alert, and language. Issues on inability to receive KPAS messages were categorized into authority, mobile, sending standard, mobile communication infra, etc. For the last two to three years, news on the inability issues had decreased, while news on the presentation issues had increased. This tells us that the public demand for improvement in the KPAS lies in the presentation issues. The demand for societal resolutions to the presentation issues especially on message content, transmission frequency, and reception range has soared.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1294-1297
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• 2013

본 논문은 기계학습을 통하여 특허문서를 국제 특허 분류(IPC) 기준에 따라 자동으로 분류하는 시스템에 관한 연구로 잠재 의미 색인 기법을 이용하여 분류의 성능을 높일 수 있는 방법을 제안하기 위한 연구이다. 종래 특허문서에 관한 IPC 자동 분류에 관한 연구가 단어 매칭 방식의 색인 기법에 의존해서 이루어진바가 있으나, 현대 기술용어의 발생 속도와 다양성 등을 고려할 때 특허문서들 간의 관련성을 분석하는데 있어서는 단어 자체의 빈도 보다는 용어의 개념에 의한 접근이 보다 효과적일 것이라 판단하여 잠재 의미 색인(LSI) 기법에 의한 분류에 관한 연구를 하게 된 것이다. 실험은 단어 매칭 방식의 색인 기법의 대표적인 자질선택 방법인 정보획득량(IG)과 카이제곱 통계량(CHI)을 이용했을 때의 성능과 잠재 의미 색인 방법을 이용했을 때의 성능을 SVM, kNN 및 Naive Bayes 분류기를 사용하여 분석하고, 그중 가장 성능이 우수하게 나오는 SVM을 사용하여 잠재 의미 색인에서 명사가 해당 용어의 개념적 의미 구조를 구축하는데 기여하는 정도가 어느 정도인지 평가함과 아울러, LSI 기법 이용시 최적의 성능을 나타내는 특이값의 범위를 실험을 통해 비교 분석 하였다. 분석결과 LSI 기법이 단어 매칭 기법(IG, CHI)에 비해 우수한 성능을 보였으며, SVM, Naive Bayes 분류기는 단어 매칭 기법에서는 비슷한 수준을 보였으나, LSI 기법에서는 SVM의 성능이 월등이 우수한 것으로 나왔다. 또한, SVM은 LSI 기법에서 약 3%의 성능 향상을 보였지만 Naive Bayes는 오히려 20%의 성능 저하를 보였다. LSI 기법에서 명사가 잠재적 의미 구조에 미치는 영향은 모든 단어들을 내용어로 한 경우 보다 약 10% 더 향상된 결과를 보여주었고, 특이값의 범위에 따른 성능 분석에 있어서는 30% 수준에 Rank 되는 범위에서 가장 높은 성능의 결과가 나왔다.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.11-18
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• 2009

Ajax based on Java Script receives attention as an alternative to ActiveX technology. Most portal sites in korea show a tendency to reopen existing services by combining the technology, because it supports most web browsers, and has the advantages of such a brilliant interface, excellent speed, and traffic reduction through asynchronous interaction. This paper modeled and implemented a multilingual meta-search service using the Ajax and open APIs provided by international famous sites. First, a Korean query is translated into one of the language of 54 countries around the world by Google translation API, and then the translated result is used to search the information of the social web sites such as Flickr, Youtube, Daum, and Naver. Searched results are displayed fast by dynamic loading of portion of the screen using Ajax. Our system can reduce server traffic and per-packet communications charges by preventing redundant transmission of unnecessary information.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.2
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• pp.17-22
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• 2023

In the midst of the development of science and technology based on the 4th industrial revolution, the ROK Army is moving forward with the ARMY TIGER 4.0 system, a ground combat system that combines future advanced science and technology. The system is developing around an AI-based hyper-connected ground combat system, and has mobility, intelligence, and networking as core concepts. Especially, the dronebot combat system is used as a compound word that refers to unmanned combat systems including drones and ground unmanned systems. In future battlefields, it is expected that the use of unmanned and artificial intelligence-based weapon systems will increase. During the transition to a complete unmanned system, it is a very important issue to ensure connectivity individual unmanned systems themselves or between manned and unmanned systems on the battlefield. This paper introduces the Multiplexer Allocation Problem (MAP) for effective command control and communication of UAV/UGV, and proposes a heuristic algorithm. In addition, the performance of the proposed algorithm is analyzed by comparing the solutions and computing time. Also, we discuss future research area for the MAP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.646-680
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• 2000

In this paper, we discuss the design and implementation of a concurrency control manager for a main memory DBMS(MMDBMS). Since an MMDBMS, unlike a disk-based DBMS, performs all of data update or retrieval operations by accessing main memory only, the portion of the cost for concurrency control in the total cost for a data update or retrieval is fairly high. Thus, the development of an efficient concurrency control manager highly accelerates the performance of the entire system. Our concurrency control manager employs the 2-phase locking protocol, and has the following characteristics. First, it adapts the partition, an allocation unit of main memory, as a locking granule, and thus, effectively adjusts the trade-off between the system concurrency and locking cost through the analysis of applications. Second, it enjoys low locking costs by maintaining the lock information directly in the partition itself. Third, it provides the latch as a mechanism for physical consistency of system data. Our latch supports both of the shared and exclusive modes, and maximizes the CPU utilization by combining the Bakery algorithm and Unix semaphore facility. Fourth, for solving the deadlock problem, it periodically examines whether a system is in a deadlock state using lock waiting information. In addition, we discuss various issues arising in development such as mutual exclusion of a transaction table, mutual exclusion of indexes and system catalogs, and realtime application supports.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.76-81
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• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.469-475
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• 2017

Software reliability is one of the most basic and essential problems in software development. In order to detect the software failure phenomenon, the intensity function, which is the instantaneous failure rate in the non-homogeneous Poisson process, can have the property that it is constant, non-increasing or non-decreasing independently at the failure time. In this study, was compared the reliability performance of the software reliability model using the Landely lifetime distribution with the intensity function decreasing pattern and Erlang lifetime distribution from increasing to decreasing pattern in the software product testing process. In order to identify the software failure phenomenon, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, was compared and evaluated software reliability using software failure interval time data. As a result, the reliability of the Landely model is higher than that of the Erlang distribution model. But, in the Erlang distribution model, the higher the shape parameter, the higher the reliability. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing software reliability attributes data and basic knowledge to software reliability model using software failure analysis.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.131-135
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• 2008

Nowadays various information devices using electronic technology has been released. And these digital devices will be continuously developed to make a satisfaction of customer's needs. So digital device will support network service using communication technology, so users will use the internet service anywhere, anytime. Also the networked device which is used in ubiquitous computing environment should be evaluated by new evaluation framework. Therefore previous usability evaluation framework need to reflect the characteristics of ubiquitous computing. However most of pervious research about ubiquitous computing was about conceptual issues like rules and characteristics of ubiquitous computing, so the research of usability testing and evaluation method for ubiquitous computing is rarely conducted. This research's purpose is developing the evaluation framework for ubiquitous computing device and usability model for ubiquitous computing. To develop the evaluation framework, we collect the evaluation indexes which have need used in GUI evaluation And we extract evaluation indexes for ubiquitous computing based on literature review.