A novel risk assessment and optimisation model for a multi-objective network security countermeasure selection problem

Authors:
Valentina Viduto;Carsten Maple;Wei Huang;David LóPez-PeréZ
Affiliations:
Institute for Research in Applicable Computing, University of Bedfordshire, Park Square, Luton, Bedfordshire, LU1 3JU, United Kingdom;Institute for Research in Applicable Computing, University of Bedfordshire, Park Square, Luton, Bedfordshire, LU1 3JU, United Kingdom;Institute for Research in Applicable Computing, University of Bedfordshire, Park Square, Luton, Bedfordshire, LU1 3JU, United Kingdom;Centre for Telecommunications Research, King's College London, Strand, WC2R 2LS, United Kingdom
Venue:
Decision Support Systems
Year:
2012

Citing 12
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Abstract

Budget 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.