• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.988-994
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• 2014

Software Defined Network (SDN) is a new technology in computer network area which enables user to centralize control plane. The security issue is important in computer network to protect system from attackers. SYN flooding attack is one of Distributed Denial of Service attack methods which are popular to degrade availability of targeted service on Internet. There are many methods to protect system from attackers, i.e. firewall and IDS. Even though firewall is designed to protect network system, but it cannot mitigate DDoS attack well because it is not designed to do so. To improve performance of DDOS mitigation we utilize another mechanism by using SDN technology such as OpenFlow and sFlow. The methodology of sFlow to detect attacker is by capturing and sum cumulative traffic from each agent to send to sFlow collector to analyze. When sFlow collector detect some traffics as attacker, OpenFlow controller will modify the rule in OpenFlow table to mitigate attacks by blocking attack traffic. Hence, by combining sum cumulative traffic use sFlow and blocking traffic use OpenFlow we can detect and mitigate SYN flooding attack quickly and cheaply.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.67-79
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• 2002

In this paper, observed trajectories of a vehicle platoon are viewed as one realization of a finite sequence of random trajectories. In this point of view, we develop novel and mathematically rigorous concept of traffic flow variables such as local traffic density, instantaneous traffic flow, and velocity field and investigate their nature on a general probability space of a sequence of random trajectories which represent vehicle trajectories. We present a simple model of random trajectories as an illustrative example and, derive the values of traffic flow variables based on the new definitions in this model. In particular, we construct the model for the sequence of random vehicle trajectories with a system of stochastic differential equations. Each equation of the system nay represent microscopic random maneuvering behavior of each vehicle with properly designed drift coefficient functions and diffusion coefficient functions. The system of stochastic differential equations nay generate a well-defined probability space of a sequence of random vehicle trajectories. We derive the partial differential equation for the expected cumulative plot with appropriate initial conditions. By solving the equation with numerical methods, we obtain the values of expected cumulative plot, local traffic density, and instantaneous traffic flow. In addition, we derive the partial differential equation for the expected travel time to a certain location with appropriate initial and/or boundary conditions, which is solvable numerically. We apply this model to a case of single vehicle trajectory.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.41-48
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• 2020

In this paper, a dynamic prediction algorithm using the cumulative distribution function for traffic volume is presented as a new method for predicting highway traffic rate more accurately, where an approximation function of the cumulative distribution function is obtained through numerical methods such as natural cubic spline interpolation and Levenberg-Marquardt method. This algorithm is a new structure of random number generation algorithm using the cumulative distribution function used in financial mathematics to be suitable for predicting traffic flow. It can be confirmed that if the highway traffic rate is simulated with this algorithm, the result is very similar to the actual traffic volume. Therefore, this algorithm is a new one that can be used in a variety of areas that require traffic forecasting as well as highways.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.87-94
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• 2016

PURPOSES : This study analyzed the lane-by-lane traffic flow characteristics in Korea by using real-world data, including congestion levels, for 2-, 3-, and 4-lane freeways. METHODS : On the basis of a literature review, lane flow and speed characteristics were analyzed using flow measurements and speed ratios. In addition, the effect of congestion levels on traffic flow were visualized using rescaled cumulative plots. RESULTS : Driver behavior varied depending on the congestion level. During free-flow conditions, the lane-use ratio of individual lanes varied largely, whereas during congestion, the ratio was nearly the same for all lanes (i.e., equilibrium). During maximum-flow and congestion conditions, the median lane was used more than the shoulder lane, whereas during all other conditions, the shoulder lane had a higher lane-use ratio. In 3- or 4-lane freeways, the lane-use ratio of the median lane always exceeded 1 and was the highest during free-flow conditions. CONCLUSIONS : The results of the present analysis can be used as an index to predict congestion before a lane is overcapacitated. Moreover, the results can be applied in variable lane guidance systems, such as car navigation systems and variable message displays, to control traffic flow.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.146-157
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• 2016

The objective of this study is to actualize a statistical model of the 3-detector simplification model, which was proposed to detect outbreak situations by Daganzo in 1997 and to verify the statistical appropriacy thereof. This study presents the calculation process of the 3-detector simplification model and realizes the process using a statistics program. Firstly, the model was applied using data on detector of the main highways on which there is no entrances or exits. Moreover, in order to statistically verify the 3-detector simplification model, accumulative traffics for 30 seconds period, which reflects the dynamic changes of traffics due to shock wave, were estimated for outbreak traffics and steady flow, and the error of acquired data was statistically compared with that of the actual accumulative traffics. As a result, the error ratio between steady and incident cumulative flows has reached its maximum after 2-3 hours from an accident. Moreover, the incident traffic flows by accidents and the stade flows are heterogeneous in terms of their dispersion and means.

• Journal of Korean Society of Transportation
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• v.12 no.2
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• pp.47-63
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• 1994

The purposes of this study are to identify Traffic Flow characteristics and to develop approach delay model of unsignalized intersection based on the travel speed in the conflicting area. The results of this study are as following ; 1. The cumulative frequency distributions of Left-turning speed show a few differences among approaches and they are distributed to lower range of speeds. On the other hand, those of through speed show obvious differences among bounds. The similar results also show in the analysis of Percentile speed. 2. The effectiveness of conflicting movements to travel speed in the conflicting area are analyzed using regression analysis. Left-turning speed model shows that Left-and Right-Conflicting speed. Through-speed model is also developed, when approaching through volume is less than 420vph. 3. Since the lost time due to the acceleration stop, and decelerlation is occured in the conflicting area, approach delay model is delivered using the travel speed models under the condition of small queuing delay.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.3
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• pp.428-451
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• 2010

Traffic matrix-based anomaly detection and DDoS attacks detection in networks are research focus in the network security and traffic measurement community. In this paper, firstly, a new type of unidirectional flow called IF flow is proposed. Merits and features of IF flows are analyzed in detail and then two efficient methods are introduced in our DDoS attacks detection and evaluation scheme. The first method uses residual variance ratio to detect DDoS attacks after Recursive Least Square (RLS) filter is applied to predict IF flows. The second method uses generalized likelihood ratio (GLR) statistical test to detect DDoS attacks after a Kalman filter is applied to estimate IF flows. Based on the two complementary methods, an evaluation formula is proposed to assess the seriousness of current DDoS attacks on router ports. Furthermore, the sensitivity of three types of traffic (IF flow, input link and output link) to DDoS attacks is analyzed and compared. Experiments show that IF flow has more power to expose anomaly than the other two types of traffic. Finally, two proposed methods are compared in terms of detection rate, processing speed, etc., and also compared in detail with Principal Component Analysis (PCA) and Cumulative Sum (CUSUM) methods. The results demonstrate that adaptive filter methods have higher detection rate, lower false alarm rate and smaller detection lag time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2680-2696
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• 2018

The collaborative content caching system is an effective solution developed in recent years to reduce transmission delay and network traffic. In order to decrease the service end-to-end transmission delay for future 5G ultra-dense networks (UDN), this paper proposes a novel service migration method that can guarantee the continuity of service and simultaneously reduce the traffic flow in the network. In this paper, we propose a service migration optimization model that minimizes the cumulative transmission delay within the constraints of quality of service (QoS) guarantee and network condition. Subsequently, we propose an improved firefly algorithm to solve this optimization problem. Simulation results show that compared to traditional collaborative content caching schemes, the proposed algorithm can significantly decrease transmission delay and network traffic flow.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.478-487
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• 2015

This study proposed a Variable Speed Limits(VSL) algorithm to use traffic information based on Cumulative Demand-Capacity Analysis and evaluated its performance. According to the analysis result, the total of delay consisted of 3 separate parts. There was no change in total travel time although the total of delay decreased. These effects was analysed theoretically and then, evaluated through VISSIM, a microscopic simulator. VISSIM simulation results show almost same as those of theoretical analysis. Furthermore in SSAM analysis with VISSIM simulation log, the number of high risk collisions decreased 36.0 %. However, the total delay decrease effect is not real meaning of decrease effect because the drivers' desired speed is same whether the VSL model is operated or not. Nevertheless this VSL model maintains free flow speed for longer and increases the cycle of traffic speed fluctuation. In other words, this is decrease of delay occurrence and scale. The decrease of speed gap between upstream and downstream stabilizes the traffic flow and leads decrease number of high risk collision. In conclusion, we can expect increase of safety through total delay minimization according to this VSL model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.249-257
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• 2017

Filtering the data for travel time records obtained from DSRC probes is essential for a better estimation of the link travel time. This study addresses the major deficiency in the performance of TRANSGUIDE in removing anomalous data. This algorithm is unable to handle unstable traffic flow conditions for certain time intervals, where fluctuations are observed. In this regard, this study proposes an algorithm that is capable of overcoming the weaknesses of TRANSGUIDE. If TRANSGUIDE fails to validate sufficient number of observations inside one time interval, another process specifies a new validity range based on the median absolute deviation (MAD), a common statistical approach. The proposed algorithm suggests the parameters, ${\alpha}$ and ${\beta}$, to consider the maximum allowed outlier within a one-time interval to respond to certain traffic flow conditions. The parameter estimation relies on historical data because it needs to be updated frequently. To test the proposed algorithm, the DSRC probe travel time data were collected from a multilane highway road section. Calibration of the model was performed by statistical data analysis through using cumulative relative frequency. The qualitative evaluation shows satisfactory performance. The proposed model overcomes the deficiency associated with the rapid change in travel time.