• Journal of Internet Computing and Services
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• v.7 no.3
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• pp.53-60
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• 2006

As it has been continuously increased the volume of traffic over Internet, it is hard for a network traffic monitoring system to analysis every packet in a real-time manner. While it is increased usage of applications which are dynamically allocated port number such as peer-to-peer(P2P), steaming media, messengers, users want to analyze traffic data generated from them. This high level analysis of each packet needs more processing time. This paper proposes to introduce load shedder for limiting the number of packets. After it determines what application generates a selected packet, the packet is analyzed with a defined application protocol.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.477-482
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• 2010

Recently, advanced Internet applications such as Internet telephone, multimedia streaming, and file sharing have appeared. Especially, P2P or web-based file sharing applications have been notorious for their illegal usage of contents and massive traffic consumption by a few users. This paper presents a novel method to identify the P2P or web-based file names with traffic monitoring. For this purpose, we have utilized the Korean decoding method on the IP packet payload. From experiments, we have shown that the file names requested by BitTorrent, Clubbox, and Tple applications could be correctly identified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2261-2280
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• 2014

Recently, network traffic has become more complex and diverse due to the emergence of new applications and services. Therefore, the importance of application-level traffic classification is increasing rapidly, and it has become a very popular research area. Although a lot of methods for traffic classification have been introduced in literature, they have some limitations to achieve an acceptable level of performance in real-time application-level traffic classification. In this paper, we propose a novel application-level traffic classification method using payload size sequence (PSS) signature. The proposed method generates unique PSS signatures for each application using packet order, direction and payload size of the first N packets in a flow, and uses them to classify application traffic. The evaluation shows that this method can classify application traffic easily and quickly with high accuracy rates, over 99.97%. Furthermore, the method can also classify application traffic that uses the same application protocol or is encrypted.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.41-60
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• 2018

Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.

• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.205-214
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• 2010

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic classification becomes important for the effective use of network resources. In this paper, we present an application traffic classification method based on fixed IP-port information. A fixed IP-port is a {IP address, port number, transport protocol}triple dedicated to only one application, which is automatically collected from the behavior analysis of individual applications. We can classify the Internet traffic more accurately and quickly by simple packet header matching to the collected fixed IP-port information. Therefore, we can construct a lightweight, fast, and accurate real-time traffic classification system than other classification method. In this paper we propose a novel algorithm to extract the fixed IP-port information and the system architecture. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.370-375
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• 2008

Automatic Identification System (AIS) is recently introduced to the maritime navigation systems. It is aimed to increase safety of vessels at sea by exchanging information to coastal monitoring stations. This article presents a ship traffic monitoring system by using the AIS information communication system using MS Visual C++. Then, the mobile Internet AIS introduced here is considerably improving and extending AIS functionalities compared to VHF AIS. When each ship is connected to the Internet network through the developed AIS system with her own client ID, all of her AIS information is surely sent to a server at her own base station by processing the information via the Internet network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.350-359
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• 2014

With the rapid growth of Internet, the importance of application traffic analysis is increasing for efficient network management. The statistical information in traffic flows can be efficiently utilized for application traffic identification. However, the packet out-of-order and retransmission occurred at the traffic collection point reduces the performance of the statistics-based traffic analysis. In this paper, we propose a novel method to detect and resolve the packet out-of-order and retransmission problem in order to improve completeness and accuracy of the traffic identification. To prove the feasibility of the proposed method, we applied our method to a real traffic analysis system using statistical flow information, and compared the performance of the system with the selected 9 popular applications. The experiment showed maximum 4% of completeness growth in traffic bytes, which shows that the proposed method contributes to the analysis of heavy flow.

• Journal of KIISE:Information Networking
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• v.34 no.4
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• pp.246-255
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• 2007

Due to the bandwidth-consuming characteristics of the heavy-hitter P2P applications, it has become critical to have the capability of pinpointing and mitigating P2P traffic. Traditional port-based classification scheme is no more adequate for this purpose because of newer P2P applications, which incorporating port-hopping techniques or disguising themselves as HTTP-based Internet disk services. Alternatively, packet filtering scheme based on payload signatures suggests more practical and accurate solution for this problem. Moreover, it can be easily deployed on existing IDSes. However, it is significantly difficult to maintain up-to-date signatures of P2P applications. Hence, the automatic signature generation method is essential and will be useful for successful signature-based traffic identification. In this paper, we suggest an automatic signature generation method for Internet disk P2P applications and provide an experimental results on CNU campus network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.131-140
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• 2011

As the number of Internet users and applications is increasing, the importance of application traffic classification is growing more and more for efficient network management. While a number of methods for traffic classification have been introduced, such as signature-based and machine learning-based methods, Skype application, which uses encrypted communication on its own P2P network, is known as one of the most difficult traffic to identify. In this paper we propose a novel method to identify Skype application traffic on the fly. The main idea is to setup a list of Skype host information {IP, port} by examining the packets generated in the Skype login process and utilizes the list to identify other Skype traffic. By implementing the identification system and deploying it on our campus network, we proved the performance and feasibility of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5B
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• pp.443-450
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• 2011

The Internet has become an essential part in our modern life by providing useful information. So, the volume of Internet traffic has been increasing rapidly, which emphasizes the importance of network traffic analysis for effective network operation and management. Signature based analysis have been commonly used, but it is shown that the increase of signatures due to the increase of applications causes the performance degradation of real-time traffic analysis on high-speed network links. In this paper, we propose OS fingerprinting method for real-time traffic analysis. The previous problems can be solved by utilizing the OS information. The OS fingerprinting method for real-time traffic analysis, proposed in this paper, conducts under passive mode, and improves the limitation of a previous method such as low completeness and accuracy. In this paper, we enlarged an input data to improve completeness, and used the User-Agent field in HTTP packet to extract various OS signatures. Also, we changed an input data from packet to flow to improve accuracy.