• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.353-355
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• 2012

본 논문에서는 지능형 감시 시스템을 위한 3가지 이상행위 검출 방법을 제안한다. 단순히 직접 감시나 센서에 의존한 문제점 검출이 아닌 비전 기반 기술을 적용하여 특정지역 및 모든 감시구역에 대하여 객체의 이상 행동을 감지하는 방법들을 소개한다. 제안하는 이상행위의 분류는 배회, 도주, 특정 감시 지역 침입 3가지로 정의한다. 휘도 기반의 평균 배경 모델링 방법을 통하여 움직임 물체를 검출하고, 검출된 객체를 분석(위치, 크기, 방향, 속도) 및 정의한다. 이때 이상행위의 판단에 따라 정의된 시나리오 환경으로 구성하고 분석하였다. 제안하는 방법은 실험에 사용된 3가지 이상행위에 대해 1초 안에 검출되는 것을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.589-595
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• 2013

The agents for security surveillance are not enough for monitoring CCTV system, so the intelligent automatic surveillance system is needed. In this paper, object detection, tracking and abnormal event detection system is implemented for intelligent CCTV system. Each modules are tested on the real CCTV environment and promoted for commercialization. Abnormal event detection module and loitering detection and sudden running detection function and it's detection time is under 1 second which is satisfied level.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.329-330
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• 2019

인터넷 기술 및 통신 기술의 급격한 발전과 사물 인터넷을 기반으로 산업 구조가 재편됨에 따라 점차 지능화, 다변화 있는 보안 위협들에 대하여 기존 시스템 보안 중심의 취약성 분석 및 데이터 암호화를 통해 구성된 보안 시스템은 한계를 보이고 있다. 특히 외부 침입 방지를 위해 별도의 사설망을 구축하여 물리적으로 분리된 보안망에 대한 악성코드 유입 등의 보안 위협 발생도 꾸준히 증가하고 있으며 보안 침해 상황 발생 시 빠른 대응도 점차 어려워지고 있다. 이에 본 연구에서는 새로운 유형의 보안 취약성 탐지를 위해 기존 보안 시스템을 구성하는 리엑티브(reactive) 기법 및 휴리스틱(heuristic) 탐지 기법이 아닌 네트워크 패킷 수집 및 분석과 대상 시스템의 비지니스 모델 매칭을 통한 사용자 행위 패턴을 해석하였다. 그리고 실시간 행위 분석을 수행하여 사용자 행위 중심의 이상 징후 감시 기준을 설립함으로써 보안 위협에 대한 행위 유형 판단 기준 및 이상 감지 판단 방법에 대해 제안한다.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.25-32
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• 2015

With the increased frequency of crime such as assaults and sexual violence, the reliance on CCTV in arresting criminals has increased as well. However, CCTV, which should be monitored by human labor force at all times, has limits in terms of budget and man-power. Thereby, the interest in intelligent security system is growing nowadays. Expanding the techniques of an objects behavior recognition in previous studies, we propose a system to detect forms of violence between 2~3 objects from images obtained in CCTV. It perceives by detecting the object with the difference operation and the morphology of the background image. The determinant criteria to define violent behaviors are suggested. Moreover, provable decision metric values through measurements of the number of violent condition are derived. As a result of the experiments with the threshold values, showed more than 80% recognition success rate. A future research for abnormal behaviors recognition system in a crowded circumstance remains to be developed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12C
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• pp.744-752
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• 2011

In intelligent surveillance system, various methods for detecting abnormal behavior were proposed recently. However, most researches are not robust enough to be utilized for actual reality which often has occlusions because of assumption the researches have that individual objects can be tracked. This paper presents a novel method to detect abnormal behavior by analysing major motion of the scene for complex environment in which object tracking cannot work. First, we generate Visual Word and Visual Document from motion information extracted from input video and process them through LDA(Latent Dirichlet Allocation) algorithm which is one of document analysis technique to obtain major motion information(location, magnitude, direction, distribution) of the scene. Using acquired information, we compare similarity between motion appeared in input video and analysed major motion in order to detect motions which does not match to major motions as abnormal behavior.

• Smart Media Journal
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• v.13 no.4
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• pp.65-75
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• 2024

This paper proposes a new approach to video surveillance systems, which have become essential components in modern urban management. By utilizing blockchain and IPFS, it enhances data integrity and privacy protection. Additionally, anomaly detection and automatic video storage are enabled through object detection technology, thus improving urban safety and security. This integrated approach serves as an efficient management methodology for surveillance systems, providing city administrators and citizens with a safer and more effective monitoring environment.

• Asia Marketing Journal
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• v.11 no.3
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• pp.1-29
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• 2009

The purpose of this study is to develop a service norm construct influencing behavioral intention in a service purchasing situation and investigate how the construct is related with other constructs in the theory of planned action model. Furthermore, a moderating variable, self-monitoring concept, in the model is considered. As a result, the influence of attitude, subjective norm, and perceived control on behavioral intention were all significant. Other consumers' norm was a significant factor affecting behavioral intention. Service provider norm, however, was not significant. In addition, self-monitoring played a moderating role in the model. The implication of this study is that service company or manager should consider service customer compatibility because focal customers are conscious that they face other customer's response.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.25-27
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• 2021

With the recent development of deep learning technology, computer vision-based AI technologies have been studied to analyze the abnormal behavior of objects in image information acquired through CCTV cameras. There are many cases where surveillance cameras are installed in dangerous areas or security areas for crime prevention and surveillance. For this reason, companies are conducting studies to determine major situations such as intrusion, roaming, falls, and assault in the surveillance camera environment. In this paper, we propose a real-time abnormal behavior analysis algorithm using object detection and tracking method.

• Proceedings of KOSOMES biannual meeting
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• 2007.11a
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• pp.87-89
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• 2007

선행 연구개발한 집단감시 디지털 시스템(Group Digital Surveillance System for Fishery Safety and Security, GDSS- F2S)은 대단위 양식장에 침입하는 도적을 방어하기 위하여 레이더 추적정보와 적아식별 정보를 제공하는 시스템이다. 그러나 GDSS-F2S에서 제공하는 두 가지 정보만으로는 도적행위를 입증할 수 있는 법적 증거자료로 미흡하다. 본 논문에서는 이러한 문제점 해결방안의 하나로 CCD 카메라를 이용한 영상획득 장치를 개발하여 GDSS-F2S에 부가한 연구내용을 기술한다. 영상획득 장치 개발에 앞서, 실험지역의 지리적인 특성을 고려한 도적침입 예상경로 분석과 도적행위 시나리오를 기반으로 유효한 대응수단을 검토한 결과, 영상획득 장치가 유효한 대응수단임을 확인하였다. 영상획득 장치는 저가이변서 성능이 우수한 0.0001 룩스의 초저조도 CCD 카메라와 부가장치를 이용하여 개발하였다. 6개월 이상의 장기 현장실험을 통하여 본 연구에서 개발한 시스템을 평가한 결과, 주간은 물론 1 미터 앞도 식별할 수 없는 야간에도 차량의 행동과 번호판 및 사람의 행동과 인상착의 등의 영상정보를 확보할 수 있었다.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.279-287
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• 2005

File integrity checking is the most reliable method to examine integrity and stability of system resources. It is required to examine the whole data whenever auditing system's integrity, and its process and result depends on administrator's experience and ability. Therefore the existing method is not appropriate to intrusion response and recovery systems, which require a fast response time. Moreover file integrity checking is able to collect information about the damaged resources, without information about the person who generated the action, which would be very useful for intrusion isolation. In this paper, we propose rtIntegrit, which combines system call auditing functions, it is called Syswatcher, with file integrity checking. The rtlntegrit can detect many activities on files or file system in real-time by combining with Syswatcher. The Syswatcher audit file I/O relative system call that is specified on configuration. And it can be easily cooperated with intrusion response and recovery systems since it generates assessment data in the standard IDMEF format.