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dc.contributor.authorViduto, Valentinaen_GB
dc.contributor.authorMaple, Carstenen_GB
dc.contributor.authorHuang, Weien_GB
dc.contributor.authorLópez-Peréz, Daviden_GB
dc.date.accessioned2012-11-05T09:47:02Zen
dc.date.available2012-11-05T09:47:02Zen
dc.date.issued2012-06en
dc.identifier.citationViduto, V. et al (2012) 'A novel risk assessment and optimisation model for a multi-objective network security countermeasure selection problem' Decision Support Systems 53 (3):599-610en_GB
dc.identifier.issn0167-9236en
dc.identifier.doi10.1016/j.dss.2012.04.001en
dc.identifier.urihttp://hdl.handle.net/10547/250940en
dc.description.abstractBudget cuts and the high demand in strengthening the security of computer systems and services constitute a challenge. Poor system knowledge and inappropriate selection of security measures may lead to unexpected financial and data losses. This paper proposes a novel Risk Assessment and Optimisation Model (RAOM) to solve a security countermeasure selection problem, where variables such as financial cost and risk may affect a final decision. A Multi-Objective Tabu Search (MOTS) algorithm has been developed to construct an efficient frontier of non-dominated solutions, which can satisfy organisational security needs in a cost-effective manner.
dc.language.isoenen
dc.publisherelsen_GB
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0167923612000978en_GB
dc.subjectfinancial decision supporten_GB
dc.subjectrisk assessmenten_GB
dc.subjectcountermeasure selection problemen_GB
dc.subjectmulti-objective optimisationen_GB
dc.subjecttabu searchen_GB
dc.titleA novel risk assessment and optimisation model for a multi-objective network security countermeasure selection problemen
dc.typeArticleen
dc.identifier.journalDecision Support Systemsen_GB
html.description.abstractBudget cuts and the high demand in strengthening the security of computer systems and services constitute a challenge. Poor system knowledge and inappropriate selection of security measures may lead to unexpected financial and data losses. This paper proposes a novel Risk Assessment and Optimisation Model (RAOM) to solve a security countermeasure selection problem, where variables such as financial cost and risk may affect a final decision. A Multi-Objective Tabu Search (MOTS) algorithm has been developed to construct an efficient frontier of non-dominated solutions, which can satisfy organisational security needs in a cost-effective manner.


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