The Experts below are selected from a list of 127716 Experts worldwide ranked by ideXlab platform
Seongjin Ahn - One of the best experts on this subject based on the ideXlab platform.
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Using genetic algorithm for Network Status learning and worm virus detection scheme
Lecture Notes in Computer Science, 2006Co-Authors: Donghyun Lim, Jin Wook Chung, Seongjin AhnAbstract:This paper tries to propose the worm virus detection system that focuses on many connection attempts, more frequently occurring in the process of scanning than their common transmission processes. And this paper tries to determine the critical value of connection attempt by using the ordinary time Network traffic learning technique which applies the genetic algorithm in order to ensure accurate detection of virus, depending on the Status of Network. This system can reduce the damage from worm virus more quickly than the pattern-founded worm virus detection system because it applies the common characteristics of worm viruses to detect them, and the criteria for judgment can be altered in its application though the Network may change.
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Development of Network Status Management System including End- to-End Active Measurement
2006Co-Authors: Jinwook Seo, Jin Wook Chung, Changwoo Nam, Youngju Ahn, Seongjin AhnAbstract:Summary This paper suggests an accumulation and analysis of control Network information to utilize as information for operating and controlling table Network using continuous active Network performance measurement. Since the administrator can promptly and conveniently control Network Statuses, when a problem pops up the cause can be quickly identified and be solved in time.
Jin Wook Chung - One of the best experts on this subject based on the ideXlab platform.
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IDEAL - Using genetic algorithm for Network Status learning and worm virus detection scheme
Intelligent Data Engineering and Automated Learning – IDEAL 2006, 2006Co-Authors: Jin Wook ChungAbstract:This paper tries to propose the worm virus detection system that focuses on many connection attempts, more frequently occurring in the process of scanning than their common transmission processes. And this paper tries to determine the critical value of connection attempt by using the ordinary time Network traffic learning technique which applies the genetic algorithm in order to ensure accurate detection of virus, depending on the Status of Network. This system can reduce the damage from worm virus more quickly than the pattern-founded worm virus detection system because it applies the common characteristics of worm viruses to detect them, and the criteria for judgment can be altered in its application though the Network may change.
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Using genetic algorithm for Network Status learning and worm virus detection scheme
Lecture Notes in Computer Science, 2006Co-Authors: Donghyun Lim, Jin Wook Chung, Seongjin AhnAbstract:This paper tries to propose the worm virus detection system that focuses on many connection attempts, more frequently occurring in the process of scanning than their common transmission processes. And this paper tries to determine the critical value of connection attempt by using the ordinary time Network traffic learning technique which applies the genetic algorithm in order to ensure accurate detection of virus, depending on the Status of Network. This system can reduce the damage from worm virus more quickly than the pattern-founded worm virus detection system because it applies the common characteristics of worm viruses to detect them, and the criteria for judgment can be altered in its application though the Network may change.
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Development of Network Status Management System including End- to-End Active Measurement
2006Co-Authors: Jinwook Seo, Jin Wook Chung, Changwoo Nam, Youngju Ahn, Seongjin AhnAbstract:Summary This paper suggests an accumulation and analysis of control Network information to utilize as information for operating and controlling table Network using continuous active Network performance measurement. Since the administrator can promptly and conveniently control Network Statuses, when a problem pops up the cause can be quickly identified and be solved in time.
Donghyun Lim - One of the best experts on this subject based on the ideXlab platform.
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Using genetic algorithm for Network Status learning and worm virus detection scheme
Lecture Notes in Computer Science, 2006Co-Authors: Donghyun Lim, Jin Wook Chung, Seongjin AhnAbstract:This paper tries to propose the worm virus detection system that focuses on many connection attempts, more frequently occurring in the process of scanning than their common transmission processes. And this paper tries to determine the critical value of connection attempt by using the ordinary time Network traffic learning technique which applies the genetic algorithm in order to ensure accurate detection of virus, depending on the Status of Network. This system can reduce the damage from worm virus more quickly than the pattern-founded worm virus detection system because it applies the common characteristics of worm viruses to detect them, and the criteria for judgment can be altered in its application though the Network may change.
Kwangsue Chung - One of the best experts on this subject based on the ideXlab platform.
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A Network Adaptive SVC Streaming Protocol for Improving Video Quality
Journal of KIISE:Information Networking, 2010Co-Authors: Jong-hyun Kim, Jahon Koo, Kwangsue ChungAbstract:The existing QoS mechanisms for video streaming are short of the consideration for various user environments and the characteristic of streaming applying programs. In order to overwhelm this problem, studies on the video streaming protocols exploiting scalable video coding (SVC), which provide spatial, temporal, and qualitative scalability in video coding, are progressing actively. However, these protocols also have the problem to deepen Network congestion situation, and to lower fairness between other traffics, as they are not equipped with congestion control mechanisms. SVC based streaming protocols also have the problem to overlook the property of videos encoded in SVC, as the protocols transmit the streaming simply by extracting the bitstream which has the maximum bit rate within available bandwidth of a Network. To solve these problems, this study suggests TCP-friendly Network adaptive SVC streaming(T-NASS) protocol which considers both Network Status and SVC bitstream property. T-NASS protocol extracts the optimal SVC bitstream by calculating TCP-friendly transmission rate, and by perceiving the Network Status on the basis of packet loss rate and explicit congestion notification(ECN). Through the performance estimation using an ns-2 Network simulator, this study identified T-NASS protocol extracts the optimal bitstream as it uses TCP-friendly transmission property and perceives the Network Status, and also identified the video image quality transmitted through T-NASS protocol is improved.
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T-NASS: TCP-friendly Network adaptive SVC streaming protocol
2009 2nd IEEE International Conference on Computer Science and Information Technology, 2009Co-Authors: Jong-hyun Kim, Jahon Koo, Kwangsue ChungAbstract:The existing QoS mechanisms for video streaming are short of the consideration for various user environments and the characteristic of streaming applying programs. In order to overwhelm this problem, studies on the video streaming protocols exploiting scalable video coding (SVC), which provide spatial, temporal, and qualitative scalability in video coding, are progressing actively. However, these protocols also have the problem to deepen Network congestion situation, and to lower fairness between other traffics, as they are not equipped with congestion control mechanisms. SVC based streaming protocols also have the problem to overlook the property of videos encoded in SVC, as the protocols transmit the streaming simply by extracting the bitstream which has the maximum bit rate within available bandwidth of a Network. To solve these problems, this study suggests TCPfriendly Network adaptive SVC streaming (T-NASS) protocol which considers both Network Status and SVC bitstream property. T-NASS protocol extracts the optimal SVC bitstream by calculating TCP-friendly transmission rate, and by perceiving the Network Status on the basis of packet loss rate and explicit congestion notification (ECN). Through the performance estimation using an ns-2 Network simulator, this study identified T-NASS protocol extracts the optimal bitstream as it uses TCP-friendly transmission property and perceives the Network Status, and also identified the video image quality transmitted through T-NASS protocol is improved.
Peng Yu-xing - One of the best experts on this subject based on the ideXlab platform.
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Reserch and Implementation of Real-time Video Compression According to Network Status
Computer Engineering, 2004Co-Authors: Peng Yu-xingAbstract:For invariable frame rate, this paper presents an approach to real-time video compression according to Network Status. and it implements real- time compression algorithm in the software. In addition, it provides the simulative experimental data and experimental result. From the experiment, it may implement lead-time video compression by dynamic control to times of wavelet analysis according to Network Status. And it verifies correctness and feasibility of the proposal.
