• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.317-326
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• 2010

Nowadays, transmission bandwidth for network traffic is increasing and the type is varied such as peer-to-peer (PZP), real-time video, and so on, because distributed computing environment is spread and various network-based applications are developed. However, as PZP traffic occupies much volume among Internet backbone traffics, transmission bandwidth and quality of service(QoS) of other network applications such as web, ftp, and real-time video cannot be guaranteed. In previous research, the port-based technique which checks well-known port number and the Deep Packet Inspection(DPI) technique which checks the payload of packets were suggested for solving the problem of the P2P traffics, however there were difficulties to apply those methods to detection of P2P traffics because P2P applications are not used well-known port number and payload of packets may be encrypted. A proposed algorithm for identifying P2P heavy traffics based on flow transport parameters and behavioral characteristics can solve the problem of the port-based technique and the DPI technique. The focus of this paper is to identify P2P heavy traffic flows rather than all P2P traffics. P2P traffics are consist of two steps i)searching the opposite peer which have some contents ii) downloading the contents from one or more peers. We define P2P flow patterns on these P2P applications' features and then implement the system to classify P2P heavy traffics.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1140-1147
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• 2022

With the development of digital technology, the marine environment is expected to change rapidly. In the case of autonomous vessels, technology is being developed in many countries, and the international community has begun to discuss ways to operate it. Changes in ships cause changes in the marine traffic environment and urge changes to aids to navigation. This study aims to analyze the cyber security management awareness of VTS personnel to improve the cyber security system for aids to navigation. To this end, the current status of cyber security management was reviewed with a focus on VTS, and a survey was conducted on VTS personnel. The survey analysis used the IPA methodology, and as a result of the analysis, a clear difference was observed in the perception of cybersecurity between those with experience in security and those without experience. In addition, technical measures related to cyber-attack detection and blocking should be implemented with the highest priority. The results of this study can be used as basic data for improving the cyber security management system for aids to navigation.

• Journal of Navigation and Port Research
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• v.38 no.1
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• pp.65-71
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• 2014

Gyeongbu and Namhae expressways in the country, are the major arterial highways which are connected with the Busan port in the north-south and east-west directions, respectively, and required to study the traffic characteristics about the hourly volume factors(K-factor) by concentrated midium-size and large-size cargo trucks of 20% or higher in expressways. We therefore attempted to predict the K-factor in expressways through the correlation analysis between K-factor and K-factor estimates on the basis of the short-term VDS data collected at the basic segments of the above major expressways. As a result, power model appeared to be appropriate in predicting K-factor by the K-factor estimate based on VDS data for 7 days with a high explanatory power and validity.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.27-37
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• 2011

The IDS/IPS(Intrusion Detection/Prevention System) has been widely deployed to protect the internal network against internet attacks. Reducing the packet inspection time is one of the most important challenges of improving the performance of the IDS/IPS. Since the IDS/IPS needs to match multiple patterns for the incoming traffic, we may have to apply the multiple pattern matching schemes, some of which use finite automata, while the others use the shift table. In this paper, we first show that the performance of those schemes would degrade with various kinds of pattern sets and payload, and then propose a hybrid multiple pattern matching scheme which combines those two schemes. The proposed scheme is organized to guarantee an appropriate level of performance in any cases. The experimental results using real traffic show that the time required to do multiple pattern matching could be reduced effectively.

• Journal of the Korean Society for Railway
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• v.8 no.2
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• pp.145-154
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• 2005

Traffic accidents at highway-rail crossing result in larger social and economic damages than the accidents at the typical highway intersections. The traditional control and warning systems of the highway-rail crossing have limitations in that 1) they do not recognize the differences of the trains' arrival times because they rely on the distance-based control system, rather than the time-based one, and 2) thereby they usually cause longer delays of vehicles and pedestrians at the highway-rail crossings. The objective of this study is to develop a time-based railroad crossing control system which takes into account the speed and expected arrival time of trains. using the spot speeds and acceleration rates of trains measured at three points, the developed system was found to be able to accurately estimate the arrival time of train. VISSIM simulation package was utilized to compare system effect of the developed time-based railroad crossing control system with that of the conventional distance-based one. It was found that the developed time-based railroad crossing control system reduced the average travel time, maximum delay length, average delay time, and average number of stop-experienced vehicles as much as 7.0$\%$, 75.6$\%$, 12.7$\%$, and 60.0$\%$, respectively, compared with those from the conventional distance-based one.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.617-629
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• 2020

In order to overcome the limitations of the rule-based intrusion detection system due to changes in Internet computing environments, the emergence of new services, and creativity of attackers, network anomaly detection (NAD) using machine learning and deep learning technologies has received much attention. Most of these existing machine learning and deep learning technologies for NAD use supervised learning methods to learn a set of training data set labeled 'normal' and 'attack'. This paper presents the feasibility of the unsupervised learning AutoEncoder(AE) to NAD from data sets collecting of secured network traffic without labeled responses. To verify the performance of the proposed AE mode, we present the experimental results in terms of accuracy, precision, recall, f1-score, and ROC AUC value on the NSL-KDD training and test data sets. In particular, we model a reference AE through the deep analysis of diverse AEs varying hyper-parameters such as the number of layers as well as considering the regularization and denoising effects. The reference model shows the f1-scores 90.4% and 89% of binary classification on the KDDTest+ and KDDTest-21 test data sets based on the threshold of the 82-th percentile of the AE reconstruction error of the training data set.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.184-191
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• 2017

This paper presents cluster based hybrid spectrum sensing system for M2M services. For each cluster, secondary nodes within the transmission radius of the primary node use hard decision method through local spectrum sensing to determine whether the primary node exists. And the other secondary nodes and the secondary nodes having poor radio channel conditions judge the existence of the primary node through the soft decision method of the values obtained by performing the cooperative spectrum sensing. In the proposed hybrid spectrum sensing system, the performance according to the number of secondary nodes is analyzed with the conventional system over Rayleigh fading channel. As the number of cooperative sensing users increased to 2, 3 and 4, the cluster error probability decreased to 0.5608, 0.5252 and 0.4001 at SNR of -10[dB] respectively. Since the proposed system uses less overhead traffic, it is found that it is more effective in terms of frequency usage than the conventional system using soft decision-soft decision and soft decision-hard decision methods.