Quantitative Security Risk Assessment (SRA) Method: An empirical case study

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dc.contributor.author Bernardo, DV
dc.contributor.author Chua, B
dc.contributor.author Hoang, DB
dc.contributor.editor Abraham
dc.contributor.editor Carvalho, A
dc.contributor.editor Carlos
dc.contributor.editor Herrera, BF
dc.contributor.editor Pai, V
dc.date.accessioned 2010-05-28T09:59:55Z
dc.date.issued 2009-01
dc.identifier.citation World Congress on Nature and Biologically Inspired Computing (NaBIC'09), 2009, pp. 972 - 977
dc.identifier.isbn 978-1-4244-5612-3
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/10842
dc.description.abstract This paper introduces a novel approach to a more practical Quantitative SRA. The approach formalized in this paper is based on the methods described in various risk assessment frameworks that were described by existing international standards with adjustments combining qualitative and ranking method based on distance-based approach. The successful implementation of this approach in four organizations provides an alternative conventional means of performing a more practical Quantitative SRA, in a manner consistent with current set of standards and practices.
dc.format Esha Dutt
dc.publisher Research Publishing Services
dc.relation.isbasedon 10.1109/NABIC.2009.5393885
dc.subject AS/NZS 4360 , Distance-based method , ISO 27001 , Security Risk Assessment , ranking method
dc.subject AS/NZS 4360 , Distance-based method , ISO 27001 , Security Risk Assessment , ranking method
dc.title Quantitative Security Risk Assessment (SRA) Method: An empirical case study
dc.type Conference Proceeding
dc.parent World Congress on Nature and Biologically Inspired Computing (NaBIC'09)
dc.journal.number en_US
dc.publocation Singapore en_US
dc.publocation Singapore
dc.identifier.startpage 972 en_US
dc.identifier.endpage 977 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.conference World Congress on Nature and Biologically Inspired Computing
dc.for 0802 Computation Theory and Mathematics
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 105099 en_US
dc.personcode 020624 en_US
dc.personcode 010772 en_US
dc.percentage 70 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom World Congress on Nature and Biologically Inspired Computing en_US
dc.date.activity 20091209 en_US
dc.date.activity 2009-12-09
dc.location.activity Comibatore, India en_US
dc.location.activity Comibatore, India
dc.description.keywords AS/NZS 4360 , Distance-based method , ISO 27001 , Security Risk Assessment , ranking method en_US
dc.description.keywords AS/NZS 4360 , Distance-based method , ISO 27001 , Security Risk Assessment , ranking method
dc.staffid en_US
dc.staffid 010772 en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computing and Communications
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Systems, Management and Leadership
pubs.organisational-group /University of Technology Sydney/Strength - Human Centred Technology Design


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