Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning

碩士 === 國立中山大學 === 資訊管理學系研究所 === 90 === This study adopts large access graph algorithm and case-base reasoning approach to generalize user access patterns and diagnose network events respectively for facilitating the network management. Large access graph (LAG) algorithm discovers the frequently int...

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Main Authors: Yi-Yao Lin, 林義堯
Other Authors: Fu-ren Lin
Format: Others
Language:en_US
Published: 2002
Online Access:http://ndltd.ncl.edu.tw/handle/90787170838795625897
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spelling ndltd-TW-090NSYS53960262015-10-13T12:46:51Z http://ndltd.ncl.edu.tw/handle/90787170838795625897 Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning 以關聯存取網路及案例式推理方法檢視網路動態狀況 Yi-Yao Lin 林義堯 碩士 國立中山大學 資訊管理學系研究所 90 This study adopts large access graph algorithm and case-base reasoning approach to generalize user access patterns and diagnose network events respectively for facilitating the network management. Large access graph (LAG) algorithm discovers the frequently inter-connections among hosts to provide an overview of network access relation. The case-based reasoning (CBR) system diagnoses the instant network events with the past experience. NetFlow log data collected from the router of the dormitory network of National Sun Yat-Sen University is used for demonstrating these two methods. The evaluation results measured by recall, precision, and accuracy show that these two mechanisms are useful to support the network administer to keep track of network access relations and diagnose the network events. Fu-ren Lin 林福仁 2002 學位論文 ; thesis 57 en_US
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language en_US
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sources NDLTD
description 碩士 === 國立中山大學 === 資訊管理學系研究所 === 90 === This study adopts large access graph algorithm and case-base reasoning approach to generalize user access patterns and diagnose network events respectively for facilitating the network management. Large access graph (LAG) algorithm discovers the frequently inter-connections among hosts to provide an overview of network access relation. The case-based reasoning (CBR) system diagnoses the instant network events with the past experience. NetFlow log data collected from the router of the dormitory network of National Sun Yat-Sen University is used for demonstrating these two methods. The evaluation results measured by recall, precision, and accuracy show that these two mechanisms are useful to support the network administer to keep track of network access relations and diagnose the network events.
author2 Fu-ren Lin
author_facet Fu-ren Lin
Yi-Yao Lin
林義堯
author Yi-Yao Lin
林義堯
spellingShingle Yi-Yao Lin
林義堯
Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
author_sort Yi-Yao Lin
title Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
title_short Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
title_full Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
title_fullStr Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
title_full_unstemmed Identifying Network Dynamics with Large Access Graph and Case-Based Reasoning
title_sort identifying network dynamics with large access graph and case-based reasoning
publishDate 2002
url http://ndltd.ncl.edu.tw/handle/90787170838795625897
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