Context- and bias-free probabilistic mission impact assessment

Alexander Motzek; Ralf Möller

doi:10.1016/j.cose.2016.11.005

Context- and bias-free probabilistic mission impact assessment

Alexander Motzek^*, Ralf Möller

^*Corresponding author for this work

Institute of Information Systems

16 Citations (Scopus)

Abstract

Assessing and understanding the impact of scattered and widespread events onto a mission is a pertinacious problem. Current approaches attempting to solve mission impact assessment employ score-based algorithms leading to spurious results. We identify a fourfold problem with score-based algorithms: (1) score-based algorithms enforce deep training of experts to employed frameworks for specification (non-context-free), (2) require reference results for interpreting obtained results (non-bias-free), (3) require assessments outside of an experts’ expertise (non-local), and (4) require validation of end-results against ground truth. This paper provides a formal, mathematical model for bias- and context-free mission impact assessment. Based on a probabilistic model we reduce mission impact assessment to a well-understood mathematical problem based on definitions from local expertise and allow for a validation at data level. This is useful for areas and applications where qualitative assessments are required, such as assessments in critical infrastructures or military contexts.

Original language	English
Journal	Computers and Security
Volume	65
Pages (from-to)	166-186
Number of pages	21
ISSN	0167-4048
DOIs	https://doi.org/10.1016/j.cose.2016.11.005
Publication status	Published - 01.03.2017

Funding

This work was partly supported by the Seventh Framework Programme (FP7) of the European Commission as part of the Panoptesec integrated research project ( GA 610416 ). We would like to thank the Swedish Defence Research Agency (FOI) for providing the SMIA2011 and SMIA2012 dataset, and especially Teodor Sommestad from the FOI's Informtion & Aeronautical Systems for further helpful comments and suggestions. Appendix

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 9 Industry, Innovation, and Infrastructure

DFG Research Classification Scheme

409-06 Information Systems, Process and Knowledge Management

Access to Document

10.1016/j.cose.2016.11.005

Cite this

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AB - Assessing and understanding the impact of scattered and widespread events onto a mission is a pertinacious problem. Current approaches attempting to solve mission impact assessment employ score-based algorithms leading to spurious results. We identify a fourfold problem with score-based algorithms: (1) score-based algorithms enforce deep training of experts to employed frameworks for specification (non-context-free), (2) require reference results for interpreting obtained results (non-bias-free), (3) require assessments outside of an experts’ expertise (non-local), and (4) require validation of end-results against ground truth. This paper provides a formal, mathematical model for bias- and context-free mission impact assessment. Based on a probabilistic model we reduce mission impact assessment to a well-understood mathematical problem based on definitions from local expertise and allow for a validation at data level. This is useful for areas and applications where qualitative assessments are required, such as assessments in critical infrastructures or military contexts.

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JO - Computers and Security

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ER -

Context- and bias-free probabilistic mission impact assessment

Abstract

Funding

UN SDGs

DFG Research Classification Scheme

Access to Document

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