• The KIPS Transactions:PartC
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• v.13C no.3 s.106
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• pp.283-294
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• 2006

Hostile network traffic is often different from normal traffic in ways that can be distinguished without knowing the exact nature of the attack. In this paper, we propose a new anomaly detection method using inbound network traffic distributions. For this purpose, we first characterize the traffic of a real campus network by the distributions of IP protocols, packet length, destination IP/port addresses, TTL value, TCP SYN packet, and fragment packet. And then we introduce the concept of entropy to transform the obtained baseline traffic distributions into manageable values. Finally, we can detect the anomalies by the difference of entropies between the current and baseline distributions. In particular, we apply the well-known denial-of-service attacks to a real campus network and show the experimental results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2366-2377
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• 1997

An Adaptive Usage Parameter Control(UPC) mechanism using a Variable Token Pool(VTP) which is kind of preventive traffic control in the Asynchronous Transfer Mode(ATM) networks is described. The VTP mechanism can monitor violations of the average bit rate and burst duration as well as peak bit rate for the ON-OFF type traffic. The VTP can vary the token pool size by monitoring burst duration and silence duration for a long term. It also improves the sensitivity against the violation of burst duration and average bit rate and enables to response for the violating traffic situation quickly. The variable token pool size is varied in step size by every burst duration and silence duration. Two important parameters for controlling token pool size are Down_size and Up_size. We compare the performance of LB and JW mechanism with the proposed VTP mechanism by computer simulations. We have known that the proposed method is more effective than the previous mechanisms. It is shown that the cell loss rate of the VTP quite depends on the value of Down_size and Up_size. The two parameters should be decided as a propr value according to traffic situations.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.369-380
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• 1996

Inductive Loop Detector(ILD) has been commonly used in collecting traffic data such as occupancy time and non-occupancy time. From the data, the traffic volume and type of passing vehicle is calculated. To provide reliable data for traffic control and plan, accuracy is required in type recognition which can be utilized to determine split of traffic signal and to provide forecasting data of queue-length for over-saturation control. In this research, a new recognition model issuggested for recognizing typeof vehicle from thecollected data obtained through ILD systems. Two clustering methods, based on statistical algorithms, and one neural network clustering method were employed to test the reliability and occuracy for the methods. In a series of experiments, it was found that the new model can greatly enhance the reliability and accuracy of type recongition rate, much higher than conventional approa-ches. The model modifies the neural network clustering method and enhances the recongition accuracy by iteratively applying the algorithm until no more unclustered data remains.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.846-853
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• 2004

This paper introduces implementation of a traffic distributed processing system on the Web Sever Networking. The study used two software packages （Packet Capture and Round-Robin Test Package） to check packet quantity from Virtual Network Structure (data generator, virtual server, Serve. 1, 2, 3), and could find out traffic distribution toward Server 1, 2, and 3. The functions of implemented Round-Robin Load Balancing Monitoring System include Round-Robin testing, system monitoring, and graphical indication of data transmission/packet quantity (figures ＆ diagram). As the result of the study shows, Round-Robin Algorithm ensured definite traffic distribution, unless incoming data loads differ much. Although error levels were high in some cases, they were eventually alleviated by repeated tests for a long period of time.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1332-1335
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• 2008

In order to various service types of real time and non-real time traffic with varying requirements are transmitted over the IEEE 802.16 standard is expected to provide quality of service(QoS) researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the Multiple-RED(Random Early Detection) model, to get the performance of the best suited, we analyzes its main control parameters (max_th, min_th, max_p) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-VQSDDP(Variable Queue State Differential Drop Probability)T, is proposed to overcome M-RED's shortcoming as well as supports static max_p parameter setting values for relative and each class proportional loss differentiation. M-RED is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore max_p parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-VQSDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.602-617
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• 2014

The performance of a cognitive radio network (CRN) solely depends on how precisely the secondary users can sense the presence or absence of primary users. The incorporation of a spatial false alarm makes deriving the probability of a correct decision a cumbersome task. Previous literature performed this task for the case of a received signal under a Normal probability density function case. In this paper we enhance the previous work, including the impact of carrier frequency, the gain of antennas on both sides, and antenna heights so as to observe the robustness against noise and interference and to make the correct decision of detection. Three small scale fading channels: Rayleigh, Normal, and Weibull were considered to get the real scenario of a CRN in an urban area. The incorporation of a maximal-ratio combining and selection combing with a variation of the number of received antennas have also been studied in order to achieve the correct decision of spectral sensing, so as to serve the cognitive users. Finally, we applied the above concept to a traffic model of the CRN, which we based on a two-dimensional state transition chain.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.6-13
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• 2002

In this paper, we propose an image processing based method to measure red-time and green-time backward moving shockwave speed automatically at signalized intersections. Shockwave means the discontinuous boundary line between different vehicle traffic flows, and its moving speed is called shockwave speed which is obtain from the slope of boundary line. In this paper, we compose distance-time diagram for measuring shockwave speed automatically. By global vehicle tracking, we draw all of the vehicle moving path on distance-time diagram. We analyze the slope change pattern of curved moving path line, and compute red-time and green-time backward moving shockwave speed. We obtain the measurement result of shockwave speed, when applying above mentioned proposed method to experiment at signalized intersections, Once we can measure the shockwave speed, we could apply the result to highway ramp metering and automatic signal control at intersections effectively since we know the situation of frontal congestion easily.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.5 s.335
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• pp.5-12
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• 2005

Establishment of bandwidth and effective traffic processing are required to treat various traffics according to a rapid increase in Internet traffic. A wavelength based transferring method was introduced to support a broadband bandwidth according to this requirement, and consequently, a label processing procedure has been investigated to treat various traffics. This paper introduces a regular shape of stack structure in order to solve the present MPLS label stack processing unit, and analyzes the relationship to label merging, which is initiated between label merging inside and outside the LSP tunnel. By applying an adaptive label structure and merging point a hierarchical label, which is aroused in the GMPLS, can be uniformly simplified and improved from the perspective of cost and processing time at a node

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.92-99
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• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.