• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.721-728
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• 2013

Big data is one of the most spotlighted technological trends in these days, enabling new methods to handle huge volume of complicated data for a broad range of applications. Real-time network traffic analysis essentially deals with big data, which is comprised of different types of log data from various sensors. To tackle this problem, in this paper, we devise a big data based platform, RENTAP, to detect and analyse malicious network traffic. Focused on military network environment such as closed network for C4I systems, leading big data based solutions are evaluated to verify which combination of the solutions is the best design for network traffic analysis platform. Based on the selected solutions, we provide detailed functional design of the suggested platform.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.323-333
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• 2012

Network traffic demand is increasing explosively because of various smart equipment and services on smart era. It causes of traffic overload for wireless and wired network. Network management system is very important to control the explosion of data traffic. It uses SNMP to communicate with various network resources for management functions and creates lots of management traffic. Those are can be serious traffic congestion on a network. I propose an improving function of SNMP to minimize unnecessary traffics between manager and agent for collecting the Trend Analysis Information which is mainly used to monitor and accumulate for a specific time period in this paper. The results of test show it has compatibility with the existing SNMP and greatly decreases the amount of network traffic and response time.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.17-22
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• 2019

Network attack analysis and visualization methods using network traffic session data detect network anomalies by visualizing the sender's and receiver's IP addresses and the relationship between them. The traffic flow is a critical feature in detecting anomalies, but simply visualizing the source and destination IP addresses symmetrically from up-down or left-right would become a problematic factor for the analysis. Also, there is a risk of losing timely security situation when designing a visualization interface without considering the temporal characteristics of time-series traffic sessions. In this paper, we propose a visualization interface and analysis method that visualizes time-series traffic data by using the radial axis, divide IP addresses into network and host portions which then projects on the cylindrical coordinate system that could effectively monitor network attacks. The proposed method has the advantage of intuitively recognizing network attacks and identifying attack activity over time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.89-92
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• 1996

It is generally recognized that Video On Demand (VOD) service will become a promising interactive service in B-ISDN. We consider a hierarchical two level network architecture for VOD service. The first level consists of connected Local Video Servers(LVSs) in which a limited number of high vision programs are stored. The second level has one Central Video Server(CVS) containing all the programs served in the network. The purpose of this paper is to analyze the network traffic and to propose the storage policy for LVSs. For this purpose, we present an analysis of program storage amount in each LVS, transmission traffic volume between LVSs, and link traffic volume between CVS and LVSs, according to changing the related factors such as demand, the number of LVSs is also presented on the basis of the tradeoffs among program storage cost, link traffic cost, and transmission cost.

• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.273-279
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• 2022

Owing to the need to establish a cooperative-intelligent transport system (C-ITS) environment in the transportation sector locally and abroad, various research and development efforts such as high-tech road infrastructure, connection technology between road components, and traffic information systems are currently underway. However, the current central control center-oriented information collection and provision service structure and the insufficient road infrastructure limit the realization of the C-ITS, which requires a diversity of traffic information, real-time data, advanced traffic safety management, and transportation convenience services. In this study, a network construction method based on the existing received signal strength indicator (RSSI) selected as a comparison target, and the experimental target and the proposed intelligent edge network compared and analyzed. The result of the analysis showed that the data transmission rate in the intelligent edge network was 97.48%, the data transmission time was 215 ms, and the recovery time of network failure was 49,983 ms.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.127-131
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• 2004

In this paper, I propose the web-based network traffic monitoring system to monitor computers running MS Windows in the small-scale PC-room. The system can support network and system operation, management, expansion, and design using network analysis and diagnosis to a network administrator. The whole system consists of two parts: analysis server for collection and analysis of the network information. and supports real-time monitoring of network traffic, and the web-based interface system. a client system shows user a graphical data that analyzed a returned result from the server. This system implements web-based technology using java and contributes to enhance the effectiveness of network administrator's management activities in PC-room by controlling and monitoring.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.263-267
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.289-295
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• 2000

Traffic analysis during past years used the Poisson distribution or Markov model, assuming an exponential distribution of packet queue arrival. Recent studies, however, have shown aperiodic and burst characteristics of network traffics. Such characteristics of data traffic enable the scalability of network, QoS, optimized design, when we analyze new traffic model having a self-similar characteristic. This paper analyzes the self-similar characteristics of a small-scale mixed traffic in a network simulation, the real WAN delay time, TCP packet size, and the total network usage.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.525-544
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• 2017

With the advent of the big data era, the interest in the development of land using traffic data has increased significantly. However, the current research on traffic big data lingers around organizing or calibrating the data only. In this research, a novel method for discovering the hidden values within the traffic data through data mining is proposed. Considering the fact that traffic data and network structures have similarities, network analysis algorithms are used to find valuable information in the actual traffic volume data. The PageRank and HITS algorithms are then employed to find the centralities. While conventional methods present centralities based on uncomplicated traffic volume data, the proposed method provides more reasonable centrality locations through network analysis. Since the centrality locations that we have found carry detailed spatiotemporal characteristics, such information can be used as an objective basis for making policy decisions.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.04a
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• pp.79-81
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• 1987

The traffic characteristicsof digitalswich network depend on the structure blocking probability, path searching method and etc. This paper presents the study of TDX-1 swicth network traffic capacity by considering some decisive factors such as call processing software, switch network structrure and control schme Conclusively the study shows that the switch network of TDX-1 can handle approximately up to 1650 Erlang.