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On the Statistical Dependency of Identity Theft on Demographics

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Protecting Persons While Protecting the People (ISIPS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5661))

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Abstract

An improved understanding of the identity theft problem is widely agreed to be necessary to succeed in counter-theft efforts in legislative, financial and research institutions. In this paper we report on a statistical study about the existence of relationships between identity theft and area demographics in the US. The identity theft data chosen was the number of citizen complaints to the Federal Trade Commission in a large number of US municipalities. The list of demographics used for any such municipality included: estimated population, median resident age, estimated median household income, percentage of citizens with a high school or higher degree, percentage of unemployed residents, percentage of married residents, percentage of foreign born residents, percentage of residents living in poverty, density of law enforcement employees, crime index, and political orientation according to the 2004 presidential election. Our study findings, based on linear regression techniques, include statistically significant relationships between the number of identity theft complaints and a non-trivial subset of these demographics.

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References

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Author information

Authors and Affiliations

  1. Telcordia Technologies, Inc., One Telcordia Drive, Piscataway, NJ, 08854, USA

    Giovanni Di Crescenzo

Authors
  1. Giovanni Di Crescenzo
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Editor information

Editors and Affiliations

  1. School of Communication and Information, Rutgers University, New Brunswick, NJ, USA

    Cecilia S. Gal , Paul B. Kantor  & Michael E. Lesk ,  & 

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Di Crescenzo, G. (2009). On the Statistical Dependency of Identity Theft on Demographics. In: Gal, C.S., Kantor, P.B., Lesk, M.E. (eds) Protecting Persons While Protecting the People. ISIPS 2008. Lecture Notes in Computer Science, vol 5661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10233-2_12

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  • DOI: https://doi.org/10.1007/978-3-642-10233-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10232-5

  • Online ISBN: 978-3-642-10233-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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