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STAKCERT worm relational model for worm detection

In this paper, a new STAKCERT worm relational model is being developed based on the evaluation of the STAKCERT worm classification using the dynamic, static and statistical analysis. A case study was conducted to evaluate the effectiveness of this STAKCERT relational model. The case study result ana...

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Main Authors:	M.M., Saudi,, A.J., Cullen,, M.E., Woodward,
Format:	Conference Paper
Language:	en_US
Published:	2015
Subjects:	Dynamic analysis Relational model Static analysis and statistical analysis
Online Access:	http://ddms.usim.edu.my/handle/123456789/9242
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id	my.usim-9242
record_format	dspace
spelling	my.usim-92422015-08-26T03:55:32Z STAKCERT worm relational model for worm detection M.M., Saudi, A.J., Cullen, M.E., Woodward, Dynamic analysis Relational model Static analysis and statistical analysis In this paper, a new STAKCERT worm relational model is being developed based on the evaluation of the STAKCERT worm classification using the dynamic, static and statistical analysis. A case study was conducted to evaluate the effectiveness of this STAKCERT relational model. The case study result analysis showed that the 5 main features in the relational model play an important role in identifying the vulnerability exploited, the damage caused, the expected rate of worm propagation, the chronological flows and the detection avoidance techniques used by the worms. As such, perhaps this new relational model produced can be used as the basis for organizations and end users in detecting worm incidents. 2015-08-26T03:55:32Z 2015-08-26T03:55:32Z 2010 Conference Paper 9789-8817-0129-9 http://ddms.usim.edu.my/handle/123456789/9242 en_US
institution	Universiti Sains Islam Malaysia
building	USIM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universit Sains Islam i Malaysia
content_source	USIM Institutional Repository
url_provider	http://ddms.usim.edu.my/
language	en_US
topic	Dynamic analysis Relational model Static analysis and statistical analysis
spellingShingle	Dynamic analysis Relational model Static analysis and statistical analysis M.M., Saudi, A.J., Cullen, M.E., Woodward, STAKCERT worm relational model for worm detection
description	In this paper, a new STAKCERT worm relational model is being developed based on the evaluation of the STAKCERT worm classification using the dynamic, static and statistical analysis. A case study was conducted to evaluate the effectiveness of this STAKCERT relational model. The case study result analysis showed that the 5 main features in the relational model play an important role in identifying the vulnerability exploited, the damage caused, the expected rate of worm propagation, the chronological flows and the detection avoidance techniques used by the worms. As such, perhaps this new relational model produced can be used as the basis for organizations and end users in detecting worm incidents.
format	Conference Paper
author	M.M., Saudi, A.J., Cullen, M.E., Woodward,
author_facet	M.M., Saudi, A.J., Cullen, M.E., Woodward,
author_sort	M.M., Saudi,
title	STAKCERT worm relational model for worm detection
title_short	STAKCERT worm relational model for worm detection
title_full	STAKCERT worm relational model for worm detection
title_fullStr	STAKCERT worm relational model for worm detection
title_full_unstemmed	STAKCERT worm relational model for worm detection
title_sort	stakcert worm relational model for worm detection
publishDate	2015
url	http://ddms.usim.edu.my/handle/123456789/9242
_version_	1645152570774126592
score	13.222552

STAKCERT worm relational model for worm detection

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