Please use this identifier to cite or link to this item: http://ddms.usim.edu.my:80/jspui/handle/123456789/9242
Title: STAKCERT worm relational model for worm detection
Authors: M.M., Saudi,
A.J., Cullen,
M.E., Woodward,
Keywords: Dynamic analysis
Relational model
Static analysis and statistical analysis
Issue Date: 2010
Abstract: 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.
URI: http://ddms.usim.edu.my/handle/123456789/9242
ISBN: 9789-8817-0129-9
Appears in Collections:World Congress On Engineering 2008, Vols I-II

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