• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1181-1191
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• 2021

The pandemic has rapidly developed a non-face-to-face environment. However, the sudden transition to a non-face-to-face environment has led to new security issues in various areas. One of the new security issues is the security threat of insiders, and the zero trust security model is drawing attention again as a technology to defend against it.. Software Defined Perimeter (SDP) technology consists of various security factors, of which device validation is a technology that can realize zerotrust by monitoring insider usage behavior. But the current SDP specification does not provide a technology that can perform device validation.. Therefore, this paper proposes a device validation technology using SVDD-based abnormal behavior detection technology through user behavior monitoring in an SDP environment and presents a way to perform the device validation technology in the SDP environment by conducting performance evaluation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_1
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• pp.483-491
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• 2013

By a development of car navigation systems and mobile or positioning technology, it increases interest in location based services, especially pedestrian navigation systems. Updating of digital maps is important because digital maps are mass data and required to short updating cycle. In this paper, we proposed change detection for different network data-sets based on areal feature matching. Prior to change detection, we defined type of updating between different network data-sets. Next, we transformed road lines into areal features(block) that are surrounded by them and calculated a shape similarity between blocks in different data-sets. Blocks that a shape similarity is more than 0.6 are selected candidate block pairs. Secondly, we detected changed-block pairs by bipartite graph clustering or properties of a concave polygon according to types of updating, and calculated Fr$\acute{e}$chet distance between segments within the block or forming it. At this time, road segments of KAIS map that Fr$\acute{e}$chet distance is more than 50 are extracted as updating road features. As a result of accuracy evaluation, a value of detection rate appears high at 0.965. We could thus identify that a proposed method is able to apply to change detection between different network data-sets.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.359-360
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• 2019

본 논문에서는 2018년에 성횡한 악성코드에 대한 피해 사례를 살펴본 후 이를 적극적으로 대응하기 위한 방안을 살펴본다. 특히 가상통화 거래소에 대한 해킹 사고 및 가상화폐에 대한 지속적인 해킹 시도가 탐지되면서 관련 소식들이 언론에 지속적으로 보도되었다. 또한 이와 관련하여 PC 및 서버 자원을 몰래 훔쳐 가상통화 채굴에 사용하는 크립토재킹 공격기법도 함께 주목받았다. 랜섬웨어 부문은 갠드크랩 관련 보도가 대부분을 차지할 정도로 국내에서 지속적으로 이슈가 되었다. 또한 미국 법무부에서 최초로 북한 해커조직의 일원을 재판에 넘기면서 해커 그룹에 대한 관심이 집중되기도 했다. 2018년 전반적으로 이러한 가상통화 거래소 해킹, 크립토재킹, 랜섬웨어, 해커 그룹의 4가지 키워드를 도출하였으며, 이 중 해커 그룹은 북한과 중국의 경우를 나누어 총 5가지 주제를 통해 악성코드에 대한 주요 이슈들을 살펴본다. 본 논문에서는 이러한 악성코드의 공격을 근본적으로 해결할 수 있는 방안으로 클라이언트 측에 USB형태의 BBS(Big Bad Stick) 하드웨어를 통하여 제안하는 환경을 제안하고 안전한 서비스가 제공됨을 증명하여 본 연구가 새로운 보안성을 갖춘 시스템임을 보인다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.548-557
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• 2021

The purpose of this study was to determine the statistical usefulness of using atypical text data collected from media that are easy to collect to overcoming limits of the existing data related to economic activities of disabled people. In addition, by performing semantic network analysis, major issues by period that could not be grasped by statistical analysis were also identified. As a result, semantic network analysis revealed that the initiative of the public sector, such as the central and local government bodies, was strongly shown. On the other hand, in the private purchase sector, it was also possible to confirm the consumption revitalization trend and changes in production activities in the recent issue of Covid-19. While the term "priority purchase" had a statistically significant relation with the other two terms "vocational rehabilitation" and "employment for the disabled". For the regression results, while the term "priority purchase" had a statistically significant association with the other two terms "vocational rehabilitation" and "employment for the disabled". Further, some statistical analyses reveal that keyword data taken from media channels can serve as an alternative indicator. Implications for issue detection in the field of welfare economy for the disabled is also discussed.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.883-890
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• 2010

Illegal waste dumping is one of the major problems that the government agency monitoring water quality has to face. One solution to this problem is to find an efficient way of managing and supervising the water quality under various kinds of conditions. In this article we establish WQMA (water quality monitoring algorithm) based on the time series intervention model. It turns out thatWQMA is quite successful in detecting illegal waste dumping.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10b
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• pp.38-43
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• 2007

최근의 소프트웨어들이 다양한 기능을 갖추어가면서 점차 복잡도가 증가하고 있으며, 이에 따라 오류로부터의 복구도 어려워져 가고 있다. 이러한 변화는 소프트웨어의 자가 치유 연구에 중요한 이슈가 되고 있다. 하지만 자가 치유 방법론에서 중요한 요소 중에 하나인 모니터는 아직까지 개발자가 일일이 작성해야 하는 한계가 있다. 따라서 본 논문은 외부 자원으로 인한 오류를 탐지하는 모니터 모듈의 생성을 자동화하는 방법론을 제시하고, 이것을 적용한 소프트웨어 아키텍처를 제안한다. 본 방법론은 1) UML의 배치 다이어그램으로부터 소프트웨어와 하드웨어간의 연결을 분석하고, 2) 기술된 제약사항을 이용하여 모니터링 모듈을 자동으로 생성한다. 3) 이후 생성된 모듈을 소프트웨어 사양에 맞게 수정한 후 컴포넌트에 추가한다. 이러한 제안 방법론을 통해 기존에 수동으로 만들어야 했던 외부 자원 모니터를 자동화하는 것이 가능해 진다. 본 논문에서는 평가를 위해 제안 방법론을 비디오 회의 시스템의 클라이언트에 적용하여, 외부 자원의 오류를 올바르게 탐지해내는지 확인한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.941-944
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• 2011

컴퓨팅 환경에서 각종 보안 위협들의 핵심에는 악성 실행파일들이 있다. 전통적인 시그니처 기반의 보안 시스템들은 악의적인 실행파일들 중에서 알려지지 않은 것들에 대해서는 런타임 탐지에 어려움이 있다. 그러한 이유로 런타임 탐지를 위해 시그니처가 필요 없는 정적, 동적 분석 방법들이 다각도로 연구되어 왔으며, 특히 악성 실행파일을 실제 실행한 후 그 동작상태를 모니터링 하는 행위기반 동적 분석방법들이 많은 발전을 이루어왔다. 그러나 대부분의 행위기반 분석방법들은 단순히 몇 가지 행위나 비순차적인 분석정보를 제공하기 때문에, 차후 악성여부를 최종 판단하는 방법론에 적용하기에는 그 분석정보가 충분하지 않다. 본 논문에서는 악성 실행파일이 실행되는 동안 발생할 수 있는 행위들을 분류하고, 이를 모니터링 하는 프로토타입 프로그램을 구현하였다. 또한, 악성 실행파일을 직접 실행하는 것은 제한된 컴퓨팅 환경에서 이루어지기 때문에, 실제 악성 실행파일을 모니터링 한 결과를 토대로 행위기반 모니터링 방법이 극복해야 될 이슈들에 대해서도 언급하고 있다.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.401-410
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• 2002

Control independence has been put forward as a new significant source of instruction-level parallelism for superscalar processors. In branch prediction mechanisms, all instructions after a mispredicted branch have to be squashed and then instructions of a correct path have to be re-fetched and re-executed. This paper presents a new branch misprediction recovery mechanism to reduce the number of instructions squashed on a misprediction. Detection of control independent instructions is accomplished with the help of the static method using a profiling and the dynamic method using a control flow of program sequences. We show that the suggested branch misprediction recovery mechanism improves the performance by 2~7% on a 4-issue processor, by 4~15% on an 8-issue processor and by 8~28% on a 16-issue processor.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.541-548
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• 2016

The use of social media is already essential as a source of information for listening user's various opinions and monitoring. We define social 'risks' that issues effect negative influences for public opinion in social media. This paper aims to discriminate various linguistic features and reveal their effects for building an automatic classification model of social risks. Expecially we adopt a word embedding technique for representation of linguistic clues in risk sentences. As a preliminary experiment to analyze characteristics of individual features, we revise errors in automatic linguistic analysis. At the result, the most important feature is NE (Named Entity) information and the best condition is when combine basic linguistic features. word embedding, and word clusters within core predicates. Experimental results under the real situation in social bigdata - including linguistic analysis errors - show 92.08% and 85.84% in precision respectively for frequent risk categories set and full test set.

• Journal of Practical Agriculture & Fisheries Research
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• v.14 no.1
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• pp.3-22
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• 2012

Control independence has been put forward as a significant new source of instruction-level parallelism for superscalar processors. In branch prediction mechanisms, all instructions after a mispredicted branch have to be squashed and then instructions of a correct path have to be re-fetched and re-executed. This paper presents a new branch misprediction recovery mechanism to reduce the number of instructions squashed on a misprediction. Detection of control independent instructions is accomplished with the help of the static method using a profiling and the dynamic method using a control flow of program sequences. We show that the suggested branch misprediction recovery mechanism improves the performance by 2~7% on a 4-issue processor, by 4~15% on an 8-issue processor and by 8~28% on a 16-issue processor.