What Should Be Classified?
A Framework with Application to the Global Force Management Data Initiative
• by
• Martin C. Libicki,
• Brian A. Jackson,
• David R. Frelinger,
• Beth E. Lachman,
• Cesse Ip,
• Nidhi Kalra
http://www.rand.org/pubs/monographs/MG989.html
For its operational planning and budget programming, the Department of Defense
(DoD) needs frequent access to current, detailed data on authorized force
structures for all the services. Having users aggregate this information
themselves was difficult, time consuming, and error prone. Hence, DoD launched
the Global Force Management Data Initiative (GFM DI). While most of the data
from the GFM DI are unclassified, the fact that it facilitates data aggregation
raised concerns about what a potential adversary might be able to do with
access to it and whether it would be better to classify such data and store it
exclusively on the secure network. The authors address this question by looking
at why material should or should not be classified, concluding that
classification is warranted only (1) if it reduces the amount of information
available to adversaries, (2) if the information kept from adversaries would
tell them something they did not know, (3) if they could make better decisions
based on this information, and (4) if such decisions would harm the United
States. Using this framework, the authors balance the risks GFM DI poses
against the costs to DoD of not having this information readily available to
its own analysts. The authors conclude that overall classification is not
necessary but suggest that some limited subsets may warrant additional
protection.
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