Shuffle Up and Deal: An Application of Capture-Recapture Methods to Estimate the Size of Stolen Data Markets

Resource type
Thesis type
(Thesis) M.A.
Date created
2016-08-24
Authors/Contributors
Abstract
Often overlooked in the measurement of crime is the underlying size of offender populations. This holds true for online property crimes involving the sale, purchase, and use of stolen financial data. Despite available data suggesting that such frauds are steadily increasing, the number of actors comprising stolen data markets has yet to be determined. The current study addresses this issue using two related capture-recapture methods—Zelterman’s estimator and its extended covariate adjusted model—to estimate the population sizes of buyers, vendors, money launderers, and facilitators who are active within online marketplaces in a calendar year. Data analysis consisted of samples collected from 3 websites that facilitate financial crimes and frauds. While the observed overlap between marketplaces was rare, results indicate that websites are perhaps not distinct entities, but are better conceptualized as a collective marketplace that is much larger in size than what can otherwise be observed.
Document
Identifier
etd9797
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Copyright is held by the author.
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This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Frank, Richard
Member of collection
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etd9797_MMacdonald.pdf 1.12 MB