• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.373-376
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• 2014

최근 모바일 기기 및 무선기기의 발달로 인하여 센서 네트워크가 다양한 분야에서 응용되고 있다. 따라서 센서에서 실시간으로 발생하는 스트리밍 데이터에서 이벤트를 감지하고 분석하는 것은 중요한 연구 분야로 부각되고 있다. 단순 이벤트의 발생 조건을 빠르게 판별하기 위해 비트맵 인덱스 기반 복합 이벤트 검출 기법 등 여러 가지 방법들이 사용되고 있지만, 아직까지 이기종 센서에서 발생하는 각기 다른 형태의 데이터를 융합하여 이벤트를 검출하는 복합 이벤트 처리에 대한 연구는 미비한 실정이다. 본 논문에서는 각기 다른 형태를 가지는 스트리밍 데이터에 멤버쉽 함수를 적용하여 퍼지화 함으로서 이기종 센서에서 발생하는 데이터를 융합 처리가능하며, Quine-Mccluskey 감축기법을 통하여 규칙의 신뢰도 및 속도가 향상된 의사결정을 하는 고속 이벤트 탐지기법을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.425-427
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• 2012

본 논문에서는 상황인지 시스템에서 규칙들간에 발생하는 충돌을 실행 이전에 탐지하기 위한 기법을 소개한다. 사용자가 새로운 규칙을 입력하면, 이벤트, 조건, 액션 정보를 단계적으로 분석하여, 동일한 이벤트가 상이한 서비스를 요구하는 규칙들을 탐지한다. 이는 실행 중에 발생되는 충돌을 감소시킴으로써, 동적 충돌 탐지 및 해결 대상을 감소시킨다. 제안된 기법은 규칙 기반 상황인지 미들웨어 상에 구현되었다.

• Spatial Information Research
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• v.20 no.5
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• pp.99-109
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• 2012

Recently, due to the growth of social media and spread of smart-phone, the amount of data has considerably increased by full use of SNS (Social Network Service). According to it, the Big Data concept is come up and many researchers are seeking solutions to make the best use of big data. To maximize the creative value of the big data held by many companies, it is required to combine them with existing data. The physical and theoretical storage structures of data sources are so different that a system which can integrate and manage them is needed. In order to process big data, MapReduce is developed as a system which has advantages over processing data fast by distributed processing. However, it is difficult to construct and store a system for all key words. Due to the process of storage and search, it is to some extent difficult to do real-time processing. And it makes extra expenses to process complex event without structure of processing different data. In order to solve this problem, the existing Complex Event Processing System is supposed to be used. When it comes to complex event processing system, it gets data from different sources and combines them with each other to make it possible to do complex event processing that is useful for real-time processing specially in stream data. Nevertheless, unstructured data based on text of SNS and internet articles is managed as text type and there is a need to compare strings every time the query processing should be done. And it results in poor performance. Therefore, we try to make it possible to manage unstructured data and do query process fast in complex event processing system. And we extend the data complex function for giving theoretical schema of string. It is completed by changing the string key word into integer type with filtering which uses keyword set. In addition, by using the Complex Event Processing System and processing stream data at real-time of in-memory, we try to reduce the time of reading the query processing after it is stored in the disk.

• Convergence Security Journal
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• v.5 no.4
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• pp.1-6
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• 2005

Today the malicious approach and information threat against a network system increase and, the demage about this spread to persnal user from company. The product which provides only unit security function like an infiltration detection system and an infiltration interception system reached the limits about the composition infiltration which is being turn out dispersion anger and intelligence anger Necessity of integrated security civil official is raising its head using various security product about infiltration detection, confrontation and reverse tracking of hacker. Because of the quantity to be many analysis of the event which is transmitted from the various security product and infiltration alarm, analysis is difficult. So server is becoming the charge of their side. Consequently the dissertation will research the method to axis infiltration alarm data to solve like this problem.

• Journal of Digital Convergence
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• v.10 no.5
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• pp.223-232
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• 2012

Recently, the leakage of personal information and privacy piracy increase. The victimized case of the malicious object rapidlies increase. Most of users use the windows operating system. Recently, the Windows 7 operating system was announced. Therefore, we need to study for the intrusion response technique at the next generation operate system circumstances. The accident response technique developed till now was mostly implemented around the Windows XP or the Windows Vista. However, a new vulnerability problem will be happen in the breach process of reaction as the Windows 7 operating system is announced. In the windows operating system, the system incident event needs to be efficiently analyzed. For this, the event information generated in a system needs to be visually analyzed around the time information or the security threat weight information. Therefore, in this research, we analyzed visually about the system event information generated in the Windows 7 operating system. And the system analyzing the system incident through the visual event information analysis process was designed and implemented. In case of using the system developed in this study the more efficient accident analysis is expected to be possible.

• Information and Communications Magazine
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• v.25 no.10
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• pp.42-49
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• 2008

본고에서는 센서네트워크 기술의 역사와 배경 그리고 국방분야에 적용 가능한 센서네트워크 시스템에 대해서 기술한다. 국방 센서네트워크 시스템은 다른 센서네트워크 응용분야에 비해 유선 망 및 이동통신망 시스템에서 요구하는 신뢰성 있는 정보전달, 실시간 지원 등을 요구하고 있으며 또한 다중센서를 복합적으로 이용하여 적의 침입 또는 이벤트 발생을 100% 탐지하고 오보율 낮출 수 있는 기능을 요구한다. 본고에서는 이러한 국방 센서네트워크 시스템에서 요구하는 사항들을 만족시키기 위해 시스템의 주요 구성 요소들에서 수행해야 할 기술들, 센서 신호처리 및 식별 기술, 신뢰성 있는 패킷 전달을 위한 섹터안테나 및 섹터안테나 기반의 MAC 기술 그리고 실시간과 신뢰성 보장을 위한 라우팅 기술에 대해 논의한다.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.1-9
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• 2022

As various services are linked to IoT(Internet of Things) and portable communication terminals, cyber attacks that exploit security vulnerabilities of the devices are rapidly increasing. In particular, cyber attacks targeting heterogeneous devices in large-scale network environments through advanced persistent threat (APT) attacks are on the rise. Therefore, in order to improve the effectiveness of the response system in the event of a breach, it is necessary to apply a data enrichment mechanism for the collected artifact data to improve threat analysis and detection performance. Therefore, in this study, by analyzing the data supplementation common elements performed in the existing incident management framework for the artifacts collected for the analysis of intrusion accidents, characteristic elements applicable to the actual system were derived, and based on this, an improved accident analysis framework The prototype structure was presented and the suitability of the derived data supplementary extension elements was verified. Through this, it is expected to improve the detection performance when analyzing cyber incidents targeting artifacts collected from heterogeneous devices.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.47-60
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• 2012

Video data comes in the form of the unstructured and the complex structure. As the importance of efficient management and retrieval for video data increases, studies on the video parsing based on the visual features contained in the video contents are researched to reconstruct video data as the meaningful structure. The early studies on video parsing are focused on splitting video data into shots, but detecting the shot boundary defined with the physical boundary does not cosider the semantic association of video data. Recently, studies on structuralizing video shots having the semantic association to the video scene defined with the semantic boundary by utilizing clustering methods are actively progressed. Previous studies on detecting the video scene try to detect video scenes by utilizing clustering algorithms based on the similarity measure between video shots mainly depended on color features. However, the correct identification of a video shot or scene and the detection of the gradual transitions such as dissolve, fade and wipe are difficult because color features of video data contain a noise and are abruptly changed due to the intervention of an unexpected object. In this paper, to solve these problems, we propose the Scene Detector by using Color histogram, corner Edge and Object color histogram (SDCEO) that clusters similar shots organizing same event based on visual features including the color histogram, the corner edge and the object color histogram to detect video scenes. The SDCEO is worthy of notice in a sense that it uses the edge feature with the color feature, and as a result, it effectively detects the gradual transitions as well as the abrupt transitions. The SDCEO consists of the Shot Bound Identifier and the Video Scene Detector. The Shot Bound Identifier is comprised of the Color Histogram Analysis step and the Corner Edge Analysis step. In the Color Histogram Analysis step, SDCEO uses the color histogram feature to organizing shot boundaries. The color histogram, recording the percentage of each quantized color among all pixels in a frame, are chosen for their good performance, as also reported in other work of content-based image and video analysis. To organize shot boundaries, SDCEO joins associated sequential frames into shot boundaries by measuring the similarity of the color histogram between frames. In the Corner Edge Analysis step, SDCEO identifies the final shot boundaries by using the corner edge feature. SDCEO detect associated shot boundaries comparing the corner edge feature between the last frame of previous shot boundary and the first frame of next shot boundary. In the Key-frame Extraction step, SDCEO compares each frame with all frames and measures the similarity by using histogram euclidean distance, and then select the frame the most similar with all frames contained in same shot boundary as the key-frame. Video Scene Detector clusters associated shots organizing same event by utilizing the hierarchical agglomerative clustering method based on the visual features including the color histogram and the object color histogram. After detecting video scenes, SDCEO organizes final video scene by repetitive clustering until the simiarity distance between shot boundaries less than the threshold h. In this paper, we construct the prototype of SDCEO and experiments are carried out with the baseline data that are manually constructed, and the experimental results that the precision of shot boundary detection is 93.3% and the precision of video scene detection is 83.3% are satisfactory.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.209-216
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• 2016

In these days, considering the trend to make various information blended based on spatial information like road, buildings and geography, it is to be very important to visualize maps for showing the information efficiently. However, geometry which is composed with line, polygon commonly used on web service has limitation to express information by limit of usage as well as spending certain time to show the information via map. That's why this study develops the efficient way to visualize huge and complex spatial information. This way is to bring partial space with spatial query, and then query and expand information excluded the former area after detecting movement event based on client. When the way is implemented, it will be expected to make efficient visualization in entire system by not bringing unnecessary information but shortening spending time to show area because it just shows areas which clients want to see.