Please use this identifier to cite or link to this item: http://ddms.usim.edu.my:80/jspui/handle/123456789/9233
Title: Reverse engineering: EDOWA worm analysis and classification
Authors: M.M., Saudi
E.M., Tamil
A.J., Cullen
M.E., Woodward
M.Y.I., Idris
Keywords: Classification
Payload
Worm analysis; Worm classification
Issue Date: 1-Jan-2009
Abstract: 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.
URI: http://ddms.usim.edu.my/handle/123456789/9233
ISBN: 9789-0481-2310-0
ISSN: 1876-1100
Appears in Collections:Lecture Notes in Electrical Engineering

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