• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.730-732
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• 2001

최근 들어 버퍼오버플로우 취약성을 이용한 해킹 사례들이 늘어나고 있다. 버퍼오버플로우 공격을 탐지하는 방법은 크게 입력 데이터의 크기검사, 비정상적인 분기 금지, 비정상 행위 금지의 세가지 방식 중 하나를 취한다. 본 논문에서는 비정상적인 분기를 금지하는 방법을 살펴본 것이다. 기존의 방법은 부가적인 메모리를 필요로 하고, 컨트롤 플로우가 비정상적인 흐름을 찾기 위해 코드를 추가하고 실행함으로써 프로그램 실행시간의 저하를 단점으로 이야기할 수 있다. 본 논문에서는 부가적인 메모리 사용을 최소한으로 줄임으로 메모리 낭비를 저하시키고 실행시간에 컨트롤 플로우가 비정상적으로 흐르는 것을 막기 위한 작업들을 최소화 함으로서 기존의 방법보다 더 효율적인 방법을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.139-142
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• 2015

데이터 센터에서는 물리적인 규모 증가와는 달리 별도의 처리 없이는 분산처리 프레임워크가 동일한 클러스터 내에서 복수로 동작할 수 없어 전체 환경을 정적으로 분할하여 이들을 배치하는 것이 일반적이다. 그러나 최근 연구에서는 복수의 프레임워크를 한 클러스터 내에서 동작시킴으로써 클러스터의 활용률을 높이는 방향으로 이루어지고 있다. Mesos는 복수의 분산처리 프레임워크를 한 클러스터에서 동작시키기 위한 시스템 중 하나로 각 프레임워크 스케줄러의 스케줄링을 지원하는 단일 Allocation Module을 가진다. Allocation Module은 모든 Slave와 프레임워크 스케줄러들의 요청을 처리하는데, 시스템 규모가 커질수록 Allocation Module으로 집중되는 부하가 증가하여 이에 따른 할당 속도 저하로 정상적인 동작이 불가능해진다. 이 문제를 해결하기 위해 본 논문에서는 Mesos 시스템의 Allocation Module 병렬화를 제안한다. 제안 방식을 통해 Allocation Module의 부하를 분산함과 동시에 Head-of-line Blocking으로 인한 스케줄링 지연 문제를 해결할 수 있을 것이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.133-134
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• 2019

최근 들어 다양한 초 고화질 스트리밍 서비스의 보급과 통신기술의 급격한 발전에 따라 고화질 비디오 신호를 포함하는 멀티미디어 데이터의 이용과 전송의 중요성이 급속도로 증가하고 있으며, 동시에 동영상에 대한 수요도 지속적으로 증가하고 있어, 더욱 효과적인 동영상의 압축기법이 요구되고 있는 실정이다. 본 논문에서는 최근 VVC 표준화 회의에서 채택된 다중 변환 선택 기술의 적용범위를 확장하여 기존의 방법처럼 휘도채널에 적용하는 것뿐만 아니라 특정한 조건 하에서는 동일한 방법을 색차채널에도 적용하도록 하여 압축 효율을 향상하는 방법을 연구하였다. 실험결과, 기존 VVC 방법 대비 BDBR 측면에서 Y(0.00 %), Cb(-0.26%), Cr(0.08%)의 결과를 얻을 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.354-356
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• 2021

For science applications that requires rapid transfer and sharing of large volume data, many efforts to improve data transfer performance have been made based on concurrency, parallelism and pipelining in data transfer applications such as Globus/GridFTP. In this paper, as a similar trial, experiments have been conducted for the expected transfer throughput enhancement by the increased number of network interface and parallelism in the Mptcp emulation environment and the result is presented.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.638-644
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• 2018

Relay systems have recently gained attentions because of its capability of cell coverage extension and the power gain as the one of key technologies for 5G. Relays can be exploited for small-cell base stations and the autonomous network, where communication devices communicate with each other cooperatively. Therefore, the relay technology is expected to enable the low power and large capacity communication. In order to maximize the benefits of using a limited number of relays, the efficient relay selection method is required. Especially, when two nodes exchange their data with each other via relay, the relay selection can maximize the average data rate by the spatial location of the relay. For this purpose, the average data rate is analyzed first according to the relay selection. In this paper, we analyzed the average data rate when two nodes exchange their data via dual-hop decode and forward relaying considering the interference by the concurrent transmission under Nakagami-m fading channel. The correctness of the analysis is verified by the Monte Carlo simulation. The results show that the concurrent transmission is superior to the non-concurrent transmission in the high required data rate region rather than in the low required data rate region.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.10
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• pp.2696-2707
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• 2009

Although, a number of DBMS vendors are scrambling to extend their products to handle XML, there is a need for a lightweight, DBMS and platform-independent XML repository as well. In this paper, we describe such an XML integrated repository system, that solves the following functions : generating relational schema from XML DTDs for storage of XML documents, importing data from XML documents into relational tables, creating XML documents according to a XMLQL(XML Query Language) from data extracted from a database and synchronizing the replicated XML documents. In the XML repository systems, the efficient change detection techniques for XML documents is required to maintain the consistency of replicated XML data because the same data in the repository can be replicated between so many different XML documents. In this paper, we propose a message digest based change detection technique to maintain the consistency of replicated data between client XML documents and a XML data in XML repository systems.

• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• KIISE Transactions on Computing Practices
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• v.21 no.3
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• pp.239-246
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• 2015

QR(Quick Response) Code has been developed to provide greater storage capacity and more functionality compared to 1D bar codes. With the emergence of increasingly mobile devices equipped with cameras such as smart-phones and tablets, QR codes have become very popular and more important in mobile businesses. Typically, most QR codes are used as a URL link for redirecting users to webpages. However, the URL based QR codes are required to be connected over the internet and to be run a server. This can incur unnecessary traffics in the Internet. Furthermore, it is not suitable for the country lagging behind others in its network infrastructure. In this paper, we propose a server-less ${\mu}$-webpage to provide mobile web services and be optimized for the capabilities and limitations of QR Code. We have implemented the ${\mu}$-webpage in Android, and the results showed that the proposed mechanism can provide web-services without requiring extra servers or incurring mobile traffic data compared to the URL-based QR Codes.

• The Journal of Bigdata
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• v.5 no.1
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• pp.41-54
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• 2020

With the recent expansion of Internet channels and the development of financial technology and information and communication technology, direct overseas purchases have expanded. Although direct overseas purchases dominate consumers in terms of price and scarcity by providing relatively low-priced products and products that are difficult to obtain in Korea, there is a higher chance of consumer dissatisfaction in terms of delivery, product, A/S and refund than domestic purchases. Therefore, this study analyzed consumer dissatisfaction caused by active overseas direct purchase and studied ways to improve problems with overseas direct purchase. As a research method, Several statistical data were collected from the Korea Consumer Agency(KCA), the Korea Customs Service(KCS) and the Korea International Trade Association(KITA) and analyzed using the Exploratory Data Analysis Technique (EDA). The analysis confirmed that consumers were not well aware of information about direct overseas purchases and that the type or degree of consumer complaints varied depending on the type of purchase. Therefore, this study suggests a direction for the revitalization of overseas direct purchases by using EDA to identify the overall status of overseas direct purchases and consumer dissatisfaction and to improve them.