Abstract
About 20 years ago, the surprising research by Latanya Sweeney demonstrated that publicly available database information exposed the overwhelming percentage of United States residents to information easily available in order to facilitate the capture of such personal information, through techniques we now refer to as “dumpster diving.” In particular, her research demonstrated that approximately 87% of the United States population can be identified uniquely using only the five-digit postal code, date of birth (including year), and gender. Although this result has held up over time, given the demographic parameters used in developing this estimate, Sweeney’s technique made no attempt to develop similar estimates for other countries. In this paper, we use Sweeney’s technique in order to provide estimates of the ability of similar demographics to provide the same type of data in a number of other countries, particularly those that tend to be as susceptible to data privacy attacks as the United States.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Sweeney, L: Simple Demographics Often Identify People Uniquely. Carnegie Mellon University, Data Privacy Working Paper 3, Pittsburgh (2000)
United Nations. https://population.un.org/wpp/Download/Standard/Population/
Wikipedia. https://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users9)
Symantec, Internet Security Threat Report. ISTR 2018 vol. 3. http://resource.elq.symantec.com
World Health Organization. http://apps.who.int/gho/data/node.main.688?lang=en
Wikipedia. https://en.wikipedia.org/wiki/List_of_postal_codes
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Patterson, W., Winston-Proctor, C.E. (2020). An International Extension of Sweeney’s Data Privacy Research. In: Ahram, T., Karwowski, W. (eds) Advances in Human Factors in Cybersecurity. AHFE 2019. Advances in Intelligent Systems and Computing, vol 960. Springer, Cham. https://doi.org/10.1007/978-3-030-20488-4_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-20488-4_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20487-7
Online ISBN: 978-3-030-20488-4
eBook Packages: EngineeringEngineering (R0)