|
Quasi-identifiers are pieces of information that are not of themselves unique identifiers, but are sufficiently well correlated with an entity that they can be combined with other quasi-identifiers to create a unique identifier. Quasi-identifiers can thus, when combined, become personally identifying information. This process is called re-identification. As an example, Latanya Sweeney has shown that even though neither gender, birth dates nor postal codes uniquely identify an individual, the combination of all three is sufficient to identify 87% of individuals in the United States.〔Sweeney, Latanya. ''Simple demographics often identify people uniquely''. Carnegie Mellon University, 2000. http://dataprivacylab.org/projects/identifiability/paper1.pdf〕 The term was introduced by Tore Dalenius in 1986. 〔Dalenius, Tore. ''Finding a Needle In a Haystack or Identifying Anonymous Census Records''. Journal of Official Statistics, Vol.2, No.3, 1986. pp. 329–336. http://www.jos.nu/Articles/abstract.asp?article=23329〕 Since then, quasi-identifiers have been the basis of several attacks on released data. For instance, Sweeney linked health records to publicly available information to locate the then-governor of Massachusetts' hospital records using uniquely-identifying quasi-identifiers, 〔Anderson, Nate. '' ''Anonymized'' data really isn’t—and here’s why not''. Ars Technica, 2009. http://arstechnica.com/tech-policy/2009/09/your-secrets-live-online-in-databases-of-ruin/ 〕 〔Barth-Jones, Daniel C. ''The're-identification'of Governor William Weld's medical information: a critical re-examination of health data identification risks and privacy protections, then and now.'' Then and Now (June 4, 2012) (2012). 〕 and Sweeney, Abu and Winn used public voter records to re-identify participants in the Personal Genome Project. 〔 Sweeney, Latanya, Akua Abu, and Julia Winn. "Identifying participants in the personal genome project by name." Available at SSRN 2257732 (2013).〕 Additionally, Arvind Narayanan and Vitaly Shmatikov made use of quasi-identifiers to de-anonymize data released by Netflix. 〔Narayanan, Arvind and Shmatikov, Vitaly. ''Robust De-anonymization of Large Sparse Datasets''. The University of Texas at Austin, 2008. https://www.cs.utexas.edu/~shmat/shmat_oak08netflix.pdf〕 Motwani and Ying warn about potential privacy breaches being enabled by publication of large volumes of government and business data containing quasi-identifiers. == References == 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Quasi-identifier」の詳細全文を読む スポンサード リンク
|