• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.215-219
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• 2004

A rapid development of the network brought increasing of many damage cases by hacker's attack. In recently many network and system resources are damaged by traffic flooding attacks. For this reason, the protection of network resources by analyzing traffic on the network is on the rise. In this paper, algorithm that improves the executing time and detection rate than traffic analysis method using SNMP is proposed and implemented.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.197-204
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• 2015

In this paper, we present an algorithm for the detection of illegally parked vehicles based on a combination of some image processing algorithms. A digital camera is fixed in the illegal parking region to capture the video frames. An adaptive Gaussian mixture model (GMM) is used for background subtraction in a complex environment to identify the regions of moving objects in our test video. Stationary objects are detected by using the pixel-level features in time sequences. A stationary vehicle is detected by using the local features of the object, and thus, information about illegally parked vehicles is successfully obtained. An automatic alarm system can be utilized according to the different regulations of different illegal parking regions. The results of this study obtained using a test video sequence of a real-time traffic scene show that the proposed method is effective.

• Journal of the Korea Society of Computer and Information
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• v.17 no.4
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• pp.11-18
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• 2012

Deep packet inspection which perform pattern matching to search for malicious patterns in the packet is most computationally intensive task. Hardware-based pattern matching is required for real-time packet inspection in high-speed network. In this paper, we have designed and implemented network intrusion detection hardware as a Microblaze-based SoC using Virtex-6 FPGA, which capture the network input packet, perform hardware-based pattern matching for patterns in the Snort rule, and provide the matching result to the software. We verify the operation of the implemented system using traffic generator and real network traffic. The implemented hardware can be used in network intrusion detection system operated in wire-speed.

• International Journal of Highway Engineering
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• v.14 no.3
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• pp.77-85
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• 2012

Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center's managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system's detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system's overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability's frequency in the real accident.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.29-34
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• 2015

Traffic lights are common in cities and are important cues for the path planning of intelligent vehicles. In this paper, we propose a robust and efficient algorithm for recognizing traffic lights from video sequences captured by a low cost off-the-shelf camera. Instead of using color information for recognizing traffic lights, a shape based approach is adopted. In learning and detection phase, Histogram of Oriented Gradients (HOG) feature is used and a cascade classifier based on Adaboost algorithm is adopted as the main classifier for locating traffic lights. To decide the color of the traffic light, a technique based on histogram analysis in HSV color space is utilized. Experimental results on several video sequences from typical urban environment prove the effectiveness of the proposed algorithm.

• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.48-54
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• 2003

Recently it frequently occur that remote host or network device breaks down because of various traffic flooding attacks. This kind of attack is classified an one of the most serious attacks of it can be used to a need of other hackings. This research is gathering system's informations for detecting a traffic flooding attack using the SNMP MIB. We analyze the traffic characteristic applying the critical value commonly used in analytical procedure of traffic flooding attacks. As a result or this analysis, traffic flooding attacks have a special character of its on. The proposed algorithm in this paper would be more available to a previous detecting method and a previous protecting method.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.378-383
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• 2012

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.16-22
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• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• Convergence Security Journal
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• v.12 no.6
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• pp.69-75
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• 2012

MANET(Mobile Ad-hoc Network) is target of many attacks because of dynamic topology and hop-by-hop data transmission method. In MANET, location setting of intrusion detection system is difficult and attack detection using information collected locally is more difficult. The amount of traffic grow, intrusion detection performance will be decreased. In this paper, MANET is composed of zone form and we used random projection technique which reduces dimension without loss of information in order to perform stable intrusion detection in even massive traffic. Global detection node is used to detect attacks which are difficult to detect using only local information. In the global detection node, attack detection is performed using received information from IDS agent and pattern of nodes. k-NN and ZBIDS were experimented to evaluate performance of the proposed technique in this paper. The superiority of performance was confirmed through the experience.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.125-132
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• 2011

A hierarchical Web Security System, which is a solution to various web-based attacks, seemingly is not able to keep up with the improvement of detoured or compound attacks. In this paper, we suggest an efficient detecting scheme for web-based attacks like Malware, XSS, Creating Webshell, URL Spoofing, and Exposing Private Information through monitoring HTTP outbound traffics in real time. Our proposed scheme detects web-based attacks by comparing the outbound traffics with the signatures of HTML tag or Javascript created by the attacks. Through the verification analysis under the real-attacked environment, we show that our scheme installed in a hierarchical web security system has superior detection capability for detoured web-based attacks.