• Convergence Security Journal
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• v.9 no.4
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• pp.7-12
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• 2009

It is very difficult to completely block the DDoS attack, which paralyzes services by depleting resources or occupying the network bandwidth by transmitting a vast amount of traffic to the specific website or server from normal users' PCs that have been already infected by an outside attacker. In order to defense or endure the DDoS attack, we usually use various solutions such as IDS (Intrusion Detection System), IPS (Intrusion Prevention System), ITS (Intrusion Tolerance System), FW (Firewall), and the dedicated security equipment against DDoS attack. However, diverse types of security appliances cause the cost problem, besides, the full function of the equipments are not performed well owing to the unproper setting without considering connectivity among systems. In this paper, we present the effective connectivity of security equipments and countermeasure methodology against DDoS attack. In practice, it is approved by experimentation that this designed methdology is better than existing network structure in the efficiency of block and endurance. Therefore, we would like to propose the effective security control measures responding and enduring against discriminated DDoS attacks through this research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.562-565
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• 2022

Recently, the increasing number of overloaded vehicles on the road poses a risk to traffic safety, such as falling objects, road damage, and chain collisions due to the abnormal weight distribution, and can cause great damage once an accident occurs. However, this irregular weight distribution is not possible to be recognized with the current weight measurement system for vehicles on roads. To address this limitation, we propose to build an object detection-based AI model to identify overloaded vehicles that cause such social problems. In addition, we present a simple yet effective method to construct an object detection model for the large-scale vehicle images. In particular, we utilize the large-scale of vehicle image sets provided by open AI-Hub, which include the overloaded vehicles from the CCTV, black box, and hand-held camera point of view. We inspected the specific features of sizes of vehicles and types of image sources, and pre-processed these images to train a deep learning-based object detection model. Finally, we demonstrated that the detection performance of the overloaded vehicle was improved by about 23% compared to the one using raw data. From the result, we believe that public big data can be utilized more efficiently and applied to the development of an object detection-based overloaded vehicle detection model.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1408-1415
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• 2007

To operate Platform Screen Door (PSD) automatically, the operational data of PSD and the train must be interfaced properly. PSD and train are operated together by the signaling system in Automatic Train Operation (ATO) signaling system zone where interfaces are provided between PSD and train. However, the additional PSD interface system with train is required in train operating zone without the interface between PSD and train. For the PSD interface, the wireless communication system or the train status (train correct stop status / train door status) detection system has been used. Seoul Metro line No.2. has the PSD wireless communication system using 447MHz band RF. For the safety of PSD operation, it is required to prevent RF interference in the subway environment where many frequencies exist. In this paper, the PSD wireless communication system is developed using 2.4GHz band RF to prevent the interference of the wireless communication and increase the traffic of the PSD interface. Furthermore, the improved system can store, manage and display the PSD and train operational data using Human Machine Interface (HMI) in the train's driver cab.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.42-48
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• 2008

The architecture of WSN based Vehicle Speed Measurement System is presented in this paper from Telematics Sensor Network(TSN) to Management System. To verify the feasibility of the system, we implemented the vehicle speed measurement system and evaluated the accuracy of velocity measured by the system in our testbed, an old highway located near Kyungbu highway. The system performed over 95% of accuracy at 80kmph from the measurement. In addition, the battery life time of the sensor node was evaluated by simulation analysis with real measured current consumption profiles. Assuming the maximum average daily traffic in 2005, the battery life time is expected to be over 1.6 year from the simulation result.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.22-32
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• 2010

Increasingly advanced Information Technology (IT) has changed the operator so as to create more diversified and advanced traffic information demand. To deal with the changing demand in private sector, a concept of on-demand traffic information has been rapidly introduced. However VMS, a product of the first generation of ITS, which was designed to provide the unspecified individuals during driving the car with the basic level of traffic information by the public failed to actively change itself in such a changing pattern. This study was intended to describe the VMS system (tentatively, FM-VMS) which was further developed to accommodate the needs favoring the sophisticated PDA with the public role of providing the unspecified individuals with the equal information. FM-VMS introduced in this study is the device designed to transmit the voice and message to the drivers through the radio information device mounted on a car. A core technology is, unlike FM-DARC and RDS, the Water Making technology which directly inserts the digital signal into FM frequency in use. It's been currently used for broadcasting and security purpose. A detection rate as a result of testing FM-VMS system using Water Making technology was 90% or more in voice and message within 20m from test VMS. When a public-developed VMS information could be transmitted using FM frequency to the relatively vulnerable users (vulnerable to traffic information) in voice on a real-time basis to provide the regional traffic information, and furthermore, VMS message could be received through radio liquid using FM frequency only, it would obviously bring about the innovation in ITS as well as pave the way for creating the new added value down the road.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.320-323
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• 2014

Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.101-112
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• 2010

The recent trend of the hacking deals with all the IT infrastructure related to the profit of the companies. Presently, they attack the service itself, the source of the profit, while they tried to access to the service infrastructure through the non-service port in the past. Although they affect the service directly, it is difficult to block them with the old security solution or the old system and they threaten more and more companies with the demand of money menacing the protection of customers and the sustainable management. This paper aims to design and implement multi-platform network packet scanner targeting the exception handling network intrusion detection system which determines normal, abnormal by traffic. Linux and unix have the various network intrusion detection and packet management tools like ngrep, snort, TCPdump, but most of them are based on CUI (Character based User Interface) giving users discomfort who are not used to it. The proposed system is implemented based on GUI(Graphical User Interface) to support the intuitive and easy-to-use interface to users, and using Qt(c++) language that supports multi-platform to run on any operating system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.1-5
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• 2013

The number of pedestrians is considered essential information which can be used to control a person who makes a entrance or a exit into a building. The number of pedestrians, also, can be used to help to manage pedestrian traffic and the volume of pedestrian flow within the building. Due to the fact there is incorrect detection by occluded, shadows, and illumination, however, difficulty can arise in existing system which is for detection and counts of a person who makes a entrance or a exit into a building. In this paper, it is minimized that the change of illumination and the effect of shadow through the transmitted image from camera which is created and processed with great adaptability. The accuracy of the calculations can be increase as well by using Kalman Filter and Mean-Shift Algorithm in order to avoid overlapped counts. As a result of the test, it is proved that the count method that shows the accuracy of 95.4% should be effective for detection and counts.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.30-38
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• 2003

This paper presents an efficient region-based motion segmentation method for segmenting of moving objects in a traffic scene with a focus on a Video Monitoring System (VMS). The presented method consists of two phases: motion detection and motion segmentation. Using the adaptive thresholding technique, the differences between two consecutive frames are analyzed to detect the movements of objects in a scene. To segment the detected regions into meaningful objects which have the similar intensity and motion information, the regions are initially segmented using a k-means clustering algorithm and then, the neighboring regions with the similar motion information are merged. Since we deal with not the whole image, but the detected regions in the segmentation phase, the computational cost is reduced dramatically. Experimental results demonstrate robustness in the occlusions among multiple moving objects and the change in environmental conditions as well.