• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.322-330
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• 2011

Binary CDMA is a new standard technology for wireless communication developed by our country that makes high speed communications and good quality of services. In this paper we researched the development methods and design of a wireless CCTV System based on the Binary-CDMA technology that makes it freely installed in any place without cables and laying works.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.153-154
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• 2018

CCTV는 현재에도 다양한 분야에서 적용되어 활용하고 있다. 하지만 다양한 분야에 설치된 CCTV 시스템에는 다양한 보안 위협이 존재하는데, 공격자는 전송되는 영상데이터를 획득함으로써 카메라에 찍은 사용자의 정보를 획득할 수 있고, 이를 조작하여 사회에 혼란을 줄 수도 있다. 또한 다수의 카메라의 영상을 보관하는 서버가 공격자에 의해 해킹당하면 다수의 카메라는 공격자에 의해 제어 될 수 있다. 본 논문에서는 CCTV의 보안위협을 해결하고자 CCTV 환경에서 프록시 재암호화를 활용하여 키관리를 함으로써 서버에 저장된 영상을 재암호화하고 원하는 사용자가 암호화된 영상을 획득하여 자신의 비밀키만으로 영상을 안전하게 복호화하여 획득할 수 있다.

• Korean Security Journal
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• no.51
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• pp.199-219
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• 2017

This research examined the degree to which open-street closed-circuit television (CCTV) systems reduced crime in the vicinity of elementary schools. Information including crime dates, locations, and types around nine elementary schools in the city of Chuncheon in South Korea where the cameras had been installed was gathered and assessed. By employing the Poisson regression with "month" as the unit of analysis and controlling for the days in each month, the average monthly temperatures, and crime trends, the research results show that the CCTV installations had an impact on the reduction of total crime and serious crime. However, the same reduction effect was not observed for disorder crime. Therefore, the results of this study suggest that the employing CCTV is an effective way to control overall crime rates, especially serious crime.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.148-154
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• 2016

Video security has recently emerged as an important issue owing to CCTV video image spill accidents over the Internet. KISA recommends the use of encryption protocols for remote access through its guidelines for CCTV personal video information protection. But still, many products do not adhere to the guidelines, and those products are easily exposed to security threats, such as hacking. To solve these security vulnerabilities, this paper proposes a CCTV system that connects from remote locations, and is implemented by using secure shell (SSH) tunneling techniques. The system enhances security by transmitting encrypted data by using SSH. By using the tunneling technique, it also solves the problem of not being able to access a CCTV recorder located inside a firewall. For evaluation of the system, this paper compares various CCTV remote access schemes and security. Experimental results on the effectiveness of the system show it is possible to obtain remote access without a significant difference in transmission quality and time. Applying the method proposed in this paper, you can configure a system secure from the threats of hacking.

• Journal of Internet of Things and Convergence
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• v.5 no.1
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• pp.7-11
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• 2019

This study suggests a methodology to track crime suspects or anomalies through CCTV in order to expand the scope of CCTV use as the number of CCTV installations continues to increase nationwide in recent years. For the abnormal behavior classification, we use the existing studies to find out suspected criminals or abnormal actors, use CNN to track objects, and connect the surrounding CCTVs to each other to predict the movement path of objectified objects CCTVs in the vicinity of the path were used to share objects' sample data to track objects and to track objects. Through this research, we will keep track of criminals who can not be traced, contribute to the national security, and continue to study them so that more diverse technologies can be applied to CCTV.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.269-279
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• 2020

Traffic estimation mainly involves surveying equipment such as automatic vehicle classification, vehicle detection system, toll collection system, and personnel surveys through CCTV (Closed Circuit TeleVision), but this requires a lot of manpower and cost. In this study, we proposed a method of estimating traffic volume using deep learning and stereo CCTV to overcome the limitation of not detecting the entire vehicle in case of single CCTV. COCO (Common Objects in Context) dataset was used to train deep learning models to detect vehicles, and each vehicle was detected in left and right CCTV images in real time. Then, the vehicle that could not be detected from each image was additionally detected by using affine transformation to improve the accuracy of traffic volume. Experiments were conducted separately for the normal road environment and the case of weather conditions with fog. In the normal road environment, vehicle detection improved by 6.75% and 5.92% in left and right images, respectively, than in a single CCTV image. In addition, in the foggy road environment, vehicle detection was improved by 10.79% and 12.88% in the left and right images, respectively.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.105-116
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• 2019

Most of the public and private buildings in Korea are installing CCTV for crime prevention and follow-up action, insider security, facility safety, and fire prevention, and the number of installations is increasing each year. In the questionnaire conducted on the increasing CCTV, many reactions were positive in terms of the prevention of crime that could occur due to the installation, rather than negative views such as privacy violation caused by CCTV shooting. However, CCTV poses a lot of privacy risks, and when the image data is collected using the cloud, the personal information of the subject can be leaked. InseCam relayed the CCTV surveillance video of each country in real time, including the front camera of the notebook computer, which caused a big issue. In this paper, we introduce a system to prevent leakage of private information and enhance the security of the cloud system by processing the privacy technique on image information about a subject photographed through CCTV.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.151-156
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• 2018

In this paper, a method to classify objects in outdoor CCTV images using Convolutional Neural Network(CNN) and background subtraction is proposed. Object candidates are extracted using background subtraction and they are classified with CNN to detect objects in the image. At the end, computation complexity is highly reduced in comparison to other object detection algorithms. A database is constructed by filming alleys and playgrounds, places where crime occurs mainly. In experiments, different image sizes and experimental settings are tested to construct a best classifier detecting person. And the final classification accuracy became 80% for same camera data and 67.5% for a different camera.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.1047-1048
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• 2014

본 논문에서는 CCTV의 문제점 및 설치 취약지역의 재난 발생을 사전에 예방하기 위해 무인비행체와 객체 인식 기술에 대해 조사 및 분석하고 이를 토대로 무인비행체의 영상정보 데이터를 관제기관에서 받아와 객체 인식 및 패턴 분석을 통해 재난을 예방하는 시스템을 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.379-380
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• 2022

KAIST 캠퍼스 기반의 실습환경 구축을 위하여 캠퍼스 전체를 스마트시티 테스트베드로 사용하며 CCTV 네트워크 기반 모니터링/관제 시스템 구축, 교통, 방범, 가로등, CCTV, 교내 버스 등 인프라 통합 관제 및 보안 실습실 구축하고 교내 자율주행 기술 연구진과 실습 협력 추진을 통한 캠퍼스 기반의 실전 스마트 환경을 토대로 다각도의 보안 공격/방어 실습을 진행하고 지자체 및 컨소시엄 기업들과 산학협력 프로젝트를 진행하기 위하여 구축한 내용을 설명한다.