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Using Real Option Thinking to Improve Decision Making in Security Investment

Franqueira, Virginia. N. L., Houmb, Siv Hilde, Daneva, Maya (2010) Using Real Option Thinking to Improve Decision Making in Security Investment. In: Lecture Notes in Computer Science. On the Move to Meaningful Internet Systems: OTM 2010. 6426. pp. 619-638. Springer ISBN 978-3-642-16933-5. (doi:10.1007/978-3-642-16934-2_46) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:77199)

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Abstract

Making well-founded security investment decisions is hard: several alternatives may need to be considered, the alternatives’ space is often diffuse, and many decision parameters that are traded-off are uncertain or incomplete. We cope with these challenges by proposing a method that supports decision makers in the process of making well-founded and balanced security investment decisions. The method has two fundamental ingredients, staging and learning, that fit into a continuous decision cycle. The method takes advantage of Real Options thinking, not only to select a decision option, but also to compound it with other options in following decision iterations, after reflection on the decision alternatives previously implemented. Additionally, our method is supported by the SecInvest tool for trade-off analysis that considers decision parameters, including cost, risks, context (such as time-to-market and B2B trust), and expected benefits when evaluating the various decision alternatives. The output of the tool, a fitness score for each decision alternative, allows to compare the evaluations of the decision makers involved as well as to include learning and consequent adjustments of decision parameters. We demonstrate the method using a three decision alternatives example.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1007/978-3-642-16934-2_46
Uncontrolled keywords: Security Decision Support, Security Economics, Extended Enterprise, Bayesian Belief Network (BBN), Real Option Analysis, Outsourcing
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Virginia Franqueira
Date Deposited: 10 Oct 2019 13:44 UTC
Last Modified: 16 Nov 2021 10:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/77199 (The current URI for this page, for reference purposes)
Franqueira, Virginia. N. L.: https://orcid.org/0000-0003-1332-9115
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