Generating Cyber Intelligence (CYBINT) scenarios & solutions to address uncertainty for decision-advantage : Using Intelligence Engineering & Strategic Options Analysis
This White Paper presents in detail how the multi-methodologies of Intelligence Engineering (IE) and then Strategic Options Analysis (SOA) can be combined, offering the development of a number of scenarios and solutions to address uncertainty and generate decision-advantage in cyber contexts. The Federation-/System-of-Systems factors & indicators of PESTLE+ (Political, Economic, Social, Technological, Legal/Legislative and Environmental + Time) are all drawn upon as variables, enabling the capture of 'key actors', 'forces/factors of change' and 'possible change over time'. Recorded by IE Matrices/Maps, this work enables the establishment of a 'Problem-Space', which can be transformed into a 'Solution-Space' following SOA's pair-wise analysis that identifies consistences and/or inconsistencies between the different variable options that arise. Thereby, the potential number of scenarios/solutions is majorly reduced making the initial Problem-Space much more manageable. Comparison can then be made between the fixed reference point of an 'anchor scenario/solution' and any other scenario/solution options that might be possible, helping identify any 'outlier' that otherwise might not have occurred to participants (an 'innovative outlier'). Guiding probabilities (or likelihood of occurrence) can be ascertained and then communicated using 'estimative language'. Ultimately, several different end-users are catered for during the course of the work undertaken during this project, firmly adhering to the well-established STARC intelligence criteria of delivering specific, timely, accurate, relevant and clear results that are subsequently ready for their further consideration with substantial foresight. --- ARC White Paper (London: Analytic Research Consortium - ARC, October 2022)
Year of publication: |
[2023]
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Authors: | Svendsen, Adam ; Garvey, Bruce |
Publisher: |
[S.l.] : SSRN |
Subject: | Betriebliches Informationssystem | Business intelligence system | Künstliche Intelligenz | Artificial intelligence | Strategisches Management | Strategic management | Szenariotechnik | Scenario analysis | Risiko | Risk | IT-Kriminalität | IT crime | Datensicherheit | Data security |
Saved in:
Extent: | 1 Online-Ressource (22 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 2022 erstellt |
Other identifiers: | 10.2139/ssrn.4495254 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014360010
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