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Quantifying risk for decentralized offensive cyber operations

Authors: Klipstein, Michael S.;

Quantifying risk for decentralized offensive cyber operations

Abstract

Computer networks and the amount of information stored within government computer networks have become ubiquitous. With the possible decentralization of authorities to conduct offensive cyber operations, leaders and their respective staffs of organizations below the national level cannot adequately assess risks and consequences of these operations due to the lack of exposure, experience, and education. Compounding this problem are the heuristics and biases used in decision making when the requisite expertise is absent. This lack of understanding of risks and potentially faulty decision making presents a gap in command and control structures. This research explores the question: How effective is a simulation framework incorporating both subject matter expertise and assessments of uncertainty at overcoming the inexperience of decision makers in assessing risk and subsequent decision making within new operations? This research effort expands multi-criteria decision-making theory by accounting and incorporating both the expertise and uncertainty of the experts into the framework. This proposed framework was tested at national-level cyber organizations and CCMD exercises. The results were then compared to see if the framework could mitigate inexperience. The results are that organizations unfamiliar with cyber operations are able to assess risks at a proficiency level equivalent to an experienced organization.

Reissued 7 Sep 2017 with corrections to committee titles.

Approved for public release; distribution is unlimited.

http://archive.org/details/quantifyingriskf1094554879

Includes supplementary material.

Major, United States Army

Keywords

cyber operations, decentralization, offensive cyber operations, cyber risk, risk

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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