A Statistical Approach Towards Worm Detection Using Cross-Relation Technique

Computer networks have become an important dimension of modern organizations. Thus, ensuring that networks run at peak performance (network utilization and speed running normal without any faults) is considered a crucial step for these organizations. To achieve this goal, networks must be secure bec...

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主要作者: Anbar, Mohammed F.R.
格式: Thesis
語言:英语
出版: 2013
主題:
在線閱讀:http://eprints.usm.my/43403/
Abstract Abstract here
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author Anbar, Mohammed F.R.
author_facet Anbar, Mohammed F.R.
author_sort Anbar, Mohammed F.R.
description Computer networks have become an important dimension of modern organizations. Thus, ensuring that networks run at peak performance (network utilization and speed running normal without any faults) is considered a crucial step for these organizations. To achieve this goal, networks must be secure because security is one of the essential issues for reaching a good performance level (no faults in the network such as high rate of connection failure). However, this task is next to impossible especially when there are other issues that need to be addressed. This thesis focuses on detecting the presence of network worms in network, which is one of the most challenging problems in network security. By detecting the presence of network worms in the network, resources and services can be further protected by patching or installing security measures, such as firewalls, intrusion detection systems, or alternative computer systems.
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spelling usm-434032019-04-12T05:26:17Z http://eprints.usm.my/43403/ A Statistical Approach Towards Worm Detection Using Cross-Relation Technique Anbar, Mohammed F.R. QA75.5-76.95 Electronic computers. Computer science Computer networks have become an important dimension of modern organizations. Thus, ensuring that networks run at peak performance (network utilization and speed running normal without any faults) is considered a crucial step for these organizations. To achieve this goal, networks must be secure because security is one of the essential issues for reaching a good performance level (no faults in the network such as high rate of connection failure). However, this task is next to impossible especially when there are other issues that need to be addressed. This thesis focuses on detecting the presence of network worms in network, which is one of the most challenging problems in network security. By detecting the presence of network worms in the network, resources and services can be further protected by patching or installing security measures, such as firewalls, intrusion detection systems, or alternative computer systems. 2013-03 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/43403/1/Mohammed%20F.R.%20Anbar24.pdf Anbar, Mohammed F.R. (2013) A Statistical Approach Towards Worm Detection Using Cross-Relation Technique. PhD thesis, Universiti Sains Malaysia.
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Anbar, Mohammed F.R.
A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
thesis_level PhD
title A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
title_full A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
title_fullStr A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
title_full_unstemmed A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
title_short A Statistical Approach Towards Worm Detection Using Cross-Relation Technique
title_sort statistical approach towards worm detection using cross relation technique
topic QA75.5-76.95 Electronic computers. Computer science
url http://eprints.usm.my/43403/
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