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Reverse engineering: EDOWA worm analysis and classification

Worms have become a real threat for computer users for the past few years. Worm is more prevalent today than ever before, and both home users and system administrators need to be on the alert to protect their network or company against attacks. It is coming out so fast these days that even the most...

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Main Authors: M.M., Saudi, E.M., Tamil, A.J., Cullen, M.E., Woodward, M.Y.I., Idris
Format: Conference Paper
Language:en_US
Published: 2015
Subjects:
Classification
Payload
Worm analysis; Worm classification
Online Access:http://ddms.usim.edu.my/handle/123456789/9233
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spelling my.usim-92332015-08-26T01:54:17Z Reverse engineering: EDOWA worm analysis and classification M.M., Saudi E.M., Tamil A.J., Cullen M.E., Woodward M.Y.I., Idris Classification Payload Worm analysis; Worm classification Worms have become a real threat for computer users for the past few years. Worm is more prevalent today than ever before, and both home users and system administrators need to be on the alert to protect their network or company against attacks. It is coming out so fast these days that even the most accurate scanners cannot track all of the new ones. Indeed until now there is no specific way to classify the worm. To understand the threats posed by the worms, this research had been carried out. In this paper the researchers proposed a new way to classify the worms which later is used as the basis to build up a system which is called as the EDOWA system to detect worms attack. Details on how the new worm of classification which is called as EDOWA worm classification is produced are explained in this paper. Hopefully this new worm classification can be used as the basis model to produce a system either to detect or defend organization from worms attack. © 2009 Springer Netherlands. 2015-08-26T01:54:17Z 2015-08-26T01:54:17Z 2009-01-01 Conference Paper 9789-0481-2310-0 1876-1100 http://ddms.usim.edu.my/handle/123456789/9233 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 Classification
Payload
Worm analysis; Worm classification
spellingShingle Classification
Payload
Worm analysis; Worm classification
M.M., Saudi
E.M., Tamil
A.J., Cullen
M.E., Woodward
M.Y.I., Idris
Reverse engineering: EDOWA worm analysis and classification
description Worms have become a real threat for computer users for the past few years. Worm is more prevalent today than ever before, and both home users and system administrators need to be on the alert to protect their network or company against attacks. It is coming out so fast these days that even the most accurate scanners cannot track all of the new ones. Indeed until now there is no specific way to classify the worm. To understand the threats posed by the worms, this research had been carried out. In this paper the researchers proposed a new way to classify the worms which later is used as the basis to build up a system which is called as the EDOWA system to detect worms attack. Details on how the new worm of classification which is called as EDOWA worm classification is produced are explained in this paper. Hopefully this new worm classification can be used as the basis model to produce a system either to detect or defend organization from worms attack. © 2009 Springer Netherlands.
format Conference Paper
author M.M., Saudi
E.M., Tamil
A.J., Cullen
M.E., Woodward
M.Y.I., Idris
author_facet M.M., Saudi
E.M., Tamil
A.J., Cullen
M.E., Woodward
M.Y.I., Idris
author_sort M.M., Saudi
title Reverse engineering: EDOWA worm analysis and classification
title_short Reverse engineering: EDOWA worm analysis and classification
title_full Reverse engineering: EDOWA worm analysis and classification
title_fullStr Reverse engineering: EDOWA worm analysis and classification
title_full_unstemmed Reverse engineering: EDOWA worm analysis and classification
title_sort reverse engineering: edowa worm analysis and classification
publishDate 2015
url http://ddms.usim.edu.my/handle/123456789/9233
_version_ 1645152568744083456
score 13.222552

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