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...

Full description

Saved in:
Bibliographic Details
Main Authors: M.M., Saudi,, A.J., Cullen,, M.E., Woodward,
Format: Conference Paper
Language:en_US
Published: 2015
Subjects:
Online Access:http://ddms.usim.edu.my/handle/123456789/9242
Tags: Add Tag
No Tags, Be the first to tag this record!
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 13.214268