Publication:
Reverse engineering: EDOWA worm analysis and classification

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dc.citedby1
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorSaudi M.M.en_US
dc.contributor.authorTamil E.M.en_US
dc.contributor.authorCullen A.J.en_US
dc.contributor.authorWoodward M.E.en_US
dc.contributor.authorIdris M.Y.I.en_US
dc.date.accessioned2024-05-28T08:40:02Z
dc.date.available2024-05-28T08:40:02Z
dc.date.issued2009
dc.description.abstractWorms 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.
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-90-481-2311-7_24
dc.identifier.epage288
dc.identifier.isbn9789050000000
dc.identifier.issn18761100
dc.identifier.scopus2-s2.0-78651561290
dc.identifier.spage277
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-78651561290&doi=10.1007%2f978-90-481-2311-7_24&partnerID=40&md5=65363bb9db29ea2f516dc32eaf22798d
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9256
dc.identifier.volume39 LNEE
dc.languageEnglish
dc.language.isoen_US
dc.relation.ispartofLecture Notes in Electrical Engineering
dc.sourceScopus
dc.subjectClassificationen_US
dc.subjectPayloaden_US
dc.subjectWorm analysisen_US
dc.subjectWorm classificationen_US
dc.subjectClassificationen_US
dc.subjectComputer usersen_US
dc.subjectHome usersen_US
dc.subjectPayloaden_US
dc.subjectSystem administratorsen_US
dc.subjectWorm analysisen_US
dc.subjectWorm classificationen_US
dc.subjectElectrical engineeringen_US
dc.subjectReverse engineeringen_US
dc.subjectReengineeringen_US
dc.titleReverse engineering: EDOWA worm analysis and classification
dc.typeConference Paperen_US
dspace.entity.typePublication

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