• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.169-171
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• 2021

Image processing through cameras such as self-driving, CCTV, mobile phone security, and parking facilities is being used to solve many real-life problems. Simple classification is solved through image processing, but it is difficult to find images or in-image features of complexly mixed objects. To solve this feature point, we utilize deep learning techniques in classification, detection, and segmentation of image data so that we can think and judge closely. Of course, the results are better than just image processing, but we confirm that the results judged by the method of image segmentation using deep learning have deviations from the real object. In this paper, we study how to perform accuracy improvement through simple image processing just before outputting the output of deep learning image segmentation to increase the precision of image segmentation.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.103-108
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• 2024

In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.9-21
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• 2017

The purpose of this study is to identify the current situation and actual condition of the video security industry, The research method was based on interviews with twelve specialists, and examined the market trends, the problems of the video security industry, the improvement plan and the government promotion strategy. The problem with the domestic video security industry is that there are the decline in overseas exports and the slowdown in exports to China, insufficient measures to overcome certification barriers due to the strengthening of national certification system, domestic demand growth slowed, expansion of domestic market share of Chinese products, lack of high-tech development of domestic products, lack of expertise in technology development and operation and inadequate legislation for revitalizing the video security industry. The improvement plan is as follows. Need to implement export expansion support policy, need to build tailored response system for each country, need improvement of security related demand creation system, take measures such as domestic industrial protection policy, certification barriers and tariff barriers, induce future core technology to create high added value. The government also needs to actively support human resources development, and induce stabilization of relevant laws and institutions. This study will contribute to the development of related industries by suggesting the development direction of the video security industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.1-6
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• 2024

In this paper, we designed and implemented the security network NVR system that can flexibly use the internal network and VPN network. In general, the NVR systems that only use internal networks cannot be access from the outside, which has the disadvantage of unnecessary inspections and inability to access from the outside. External access has made possible using the VPN security network, and a NVR system software was designed and implemented so that the existing internal network could be used. We compared with the NVR system usage environment in the internal network through the client and the NVR system. It also has implemented usage environment with the VPN network through the mobile APP, and confirmed that the same NVR was operating normally with the same functions. We also studied on IP based NVR for flexible access with closed loop network based on VPN system.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.340-347
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• 2010

Though there are many crimes on and out university campus in Korea, no one knows anything about the size or the types of campus crime. But, there are many theft crimes and sex assault in the library and one-room village near the university campus. This study suggested the establish ways and means needed to improve the campus security system, with the focus on the CPTED(Crime Prevention Through Environmental Design). Various types of crime prevention methods are being considered instead of conventional crime suppression measures. Among them, CPTED is drawing global attention. Crime prevention through environmental design is a multi-disciplinary approach to deterring criminal behavior through environmental design. CPTED strategies rely upon the ability to influence offender decisions that precede criminal acts. A truly safe campus can be achieved only through the cooperation of all students, faculty, staff and visitors. The cooperation and involvement of the entire campus community in campus crime prevention is absolutely necessary. University should adopt a series of policies and procedures designed to ensure that every possible precaution is taken to protect persons and property on campus.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.31-37
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• 2015

The recent long-term economic recession and business depression are constantly increasing the occurence of the five major crimes(murder, robbery, rape, theft, violence). When looking into the previously-analyzed characteristics of how the five major crimes are committed, this study understands that the crimes mostly occur in these crime-ridden areas of poor public order and security and, in order to decrease the crime rates of the crime-prone areas, any relevant fields have been emphasizing the application of CPTED. In the light of that, referring to CPTED surveillance factors and the current crime rate data, the study presented ways to help the relevant fields draw up a crime-prone area grade map. In particular, the security center among monitoring elements was visualized by dividing it into point patrol and directed patrol and by dividing it into 3 steps monitoring levels with CCTV and street lights. In addition, we checked the crime rate by zoning through crime statistics occurred in the research areas and established a crime status map. We estimated the weight through AHP analysis on the built monitoring elements and the zoning of the occurred areas, as a result of making a map vulnerable to crime by monitoring steps by overlapping each element, we were able to confirm that 60% of theft, 52% of violence and 33% of rape in the 1st grade area were reduced compared to the 1st step in monitoring Step 3.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.77-91
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• 2019

Recent Linux operating systems having been increasingly used, ranging from automotive consoles, CCTV, IoT devices, and mobile devices to various versions of the kernel. Because these devices can be used as strong evidence in criminal investigations, there is a risk of destroying evidence through file deletion. Ext filesystem forensics has been studied in depth because it can recovery deleted files without depending on the kind of device. However, studies have been carried out without consideration of characteristics of file system which may vary depending on the kernel. This problem can lead to serious situations, such as those that can impair investigative ability and cause doubt of evidence ability, when an actual investigation attempts to analyze a different version of the kernel. Because investigations can be performed on various distribution and kernel versions of Linux file systems at the actual investigation site, analysis of the metadata changes that occur when files are deleted by Linux distribution and kernel versions is required. Therefore, in this paper, we analyze the difference of metadata according to the Linux kernel as a solution to this and recovery deleted file. After that, the investigating agency needs to consider the metadata change caused by the difference of Linux kernel version when performing Ext filesystem forensics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.111-118
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• 2023

Cyber attacks are increasing worldwide, and attacks on personal privacy such as CCTV and IP camera hacking are also increasing. If you search for IP camera hacking methods in spaces such as YouTube, SNS, and the dark web, you can easily get data and hacking programs are also on sale. If you use an IP camera that has vulnerabilities used by hacking programs, you easily get hacked even if you change your password regularly or use a complex password including special characters, uppercase and lowercase letters, and numbers. Although news and media have raised concerns about the security of IP cameras and suggested measures to prevent damage, hacking incidents continue to occur. In order to prevent such hacking damage, it is necessary to identify the cause of the hacking incident and take concrete measures. First, we analyzed weak account settings and web server vulnerabilities of IP cameras, which are the causes of IP camera hacking, and suggested solutions. In addition, as a specific countermeasure against hacking, it is proposed to add a function to receive a notification when an IP camera is connected and a function to save the connection history. If there is such a function, the fact of damage can be recognized immediately, and important data can be left in arresting criminals. Therefore, in this paper, we propose a method to increase the safety from hacking by using the connection notification function and logging function of the IP camera.